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Emerging Technology

AI in customer experience

The Role of AI in Shaping Customer Experience

Introduction

AI plays an important role in shaping customer experience across various industries and these AI technologies can help businesses to personalize their interactions with customers anticipate their needs and provide timely and relevant solutions. These AI-powered chatbots and virtual assistants can offer 24/7 support, answer customer queries and guide them through the purchasing process.

The combination of AI and predictive analytics can add a very high degree of smartness to digital marketing. The use of AI in customer segmentation is also more accurate and faster – it can reveal segments within this group that share similar characteristics. AI has the potential to significantly enhance customer experience by making interactions more convenient and efficient.

Overview of traditional customer service models and their limitations

Traditional customer service models often include in-person interactions, phone calls and email correspondence and these methods have been effective but they come with limitations. In-person interactions are limited by geographical constraints which may not be convenient for all customers.

The traditional customer service models may struggle to handle large volumes of inquiries efficiently, leading to delays and customer dissatisfaction. The lack of personalization in traditional models can result in a one-size-fits-all approach that doesn’t provide to individual customer needs.

Traditional customer service models often rely on human agents which can lead to inconsistencies in service quality and may not be cost-effective. These can address these shortcomings and adapt to the changing landscape of customer service which ultimately leads to improved customer satisfaction and loyalty.

How AI is enhancing customer experiences through personalization and blockchain

AI-powered chatbots and virtual assistants can provide – real-time, efficient customer support, reducing response times and ensuring seamless interactions which not only enhances the customer service experience but also helps businesses save costs and resources. By using AI businesses can automate repetitive tasks or personalize customer interactions it provides consistent and accurate information to their customers.

When AI and blockchain are combined they can further enhance customer experience by enabling secure, personalized transactions and interactions. For example – blockchain can be used to securely store and manage customer data also the AI can analyse this data to provide personalized recommendations and services.

The blockchain can ensure the integrity and security of AI algorithms and the data they rely on, which further improves trust and transparency in the customer experience. The combination of AI and blockchain technology can transform the customer experience.

Applications of AI in Customer Service

Businesses are accepting the technology to give customers consistent service and experience and AI is transforming customer service by improving consumer engagement and providing 24/7 customer care. AI has numerous applications in customer service that include:

  • Chatbots and Virtual Assistants – AI-powered chatbots and virtual assistants can handle customer inquiries, provide support, and offer personalized recommendations 24/7, improving response times and customer satisfaction.
  • Personalized Interactions – AI enables businesses to analyze customer data and behavior to deliver personalized interactions, such as tailored product recommendations and customized communication that enhance customer experience.
  • Predictive Analytics – AI can be used to predict customer behavior and preferences based on historical data, allowing businesses to anticipate needs, offer proactive support and optimize product offerings.
  • Sentiment Analysis – AI can analyze customer feedback, social media posts, and reviews to gauge sentiment, identify trends, and address potential issues, helping businesses improve their products and services.

These applications validate the AI by showing the transformation of customer service that provides efficient, personalized and proactive support to improve the overall customer experience.

Chatbots and Virtual Assistants

FAQ Assistance

FAQs are often displayed on websites to help people troubleshoot problems with hardware and software. They can also serve as a customer service portal that quickly provides basic information to users.

FAQ stands for Frequently Asked Questions and it has a list of common questions and answers on a particular topic related to their product or service. FAQ pages are often found on websites to provide quick answers to common questions that users may have and help users find information without having to contact customer support. FAQ pages are a helpful resource for both businesses and their customers as they can save time and provide clarity.

Businesses that benefit from FAQ pages by reorganizing customer interactions and ensuring consistent messaging also the users appreciate the accessibility and efficiency of obtaining information. Hence FAQ pages play a valuable role in knowledge-sharing between businesses and their audience.

24/7 availability using blockchain

Blockchain works 24/7 helps to eliminate the limitations of banking hours and enables continuous global payments. Blockchain has cryptographic security that measures to reduce the risk of fraud and unauthorized payment data.

Blockchain’s distributed ledger system allows for continuous access to information and services without reliance on a central authority. Smart contracts are a feature of blockchain that can automate processes and ensure around-the-clock execution of predefined actions. The blockchain contains the transparency and immutability that contribute to building trust and reliability.

There are numerous industries such as – finance, supply chain management and healthcare where the blockchain’s 24/7 availability can transform processes by allowing real-time transactions and automated operations. This has the potential to update business operations which will also reduce delays and improve customer experiences.

Predictive Analytics with blockchain 

Targeted promotions and nonce

The nonce is a significant concept in blockchain technology and it is a value that can only be used once and is commonly employed in cryptographic algorithms and authentication protocols. By incorporating nonces into blockchain transactions businesses can confirm unique and secure interactions with customers that will also enhance the integrity of targeted promotions.

AI provides the benefits of this data to personalize promotions based on individual preferences and purchasing behavior. This combination of blockchain’s security and AI’s analytical abilities can allow for more effective and personalized targeted promotions while maintaining the integrity and security of customer interactions.

Proactive issue resolution

The integration of AI and blockchain technology can allow resolution in various industries that also include education and by analyzing large amounts of data the AI algorithms can detect patterns and differences which can also detect fraud. The benefits of AI in blockchain analytics include – increased accuracy, proactive monitoring, cost savings and compliance.

Blockchain has an immutable and transparent ledger that has secure storage which is a comprehensive record of transactions and interactions and with the help of AI it can analyze this data to identify potential problems. The AI has predictive capabilities and blockchain-secure data storage and the businesses can anticipate and address issues before they escalate which leads to improved operational efficiency. Blockchain and AI allow organizations to proactively identify and resolve issues, ultimately enhancing trust, reliability and customer experience.

Computer Vision

Facial recognition for queues

Facial recognition technology can be used in lines to update the verification process and improve security and by using AI-powered facial recognition systems individuals can be identified quickly which will reduce the wait times and improve the overall experience. For example – airport industry facial recognition technology can be used to speed up the verification process for passengers, reducing wait times and improving security.

This data has been securely stored on a blockchain that allows privacy and security and AI algorithms can then analyze the facial recognition data to optimize queue management along with the prediction of wait times and assign resources efficiently.

The blockchain can provide a tamper-proof record of individual’s positions which will enhance transparency and accountability. The integration of facial recognition with blockchain and AI can enhance security along with it will improve the overall customer experience.

Object detection for inventory using blockchain

The combination of object detection using AI and blockchain technology can significantly impact inventory management and object detection facilitates automated inventory tracking, quality control and personalized shopping experiences. By combining AI-powered object detection with blockchain a transparent, distributed and reliable inventory management system can be achieved that will enhance the security and efficiency of the process.

This technology has supported businesses which has led to the automation of the process for inventory tracking, reducing human error and improving efficiency. The use of blockchain allows the inventory data to be transparent and secure which also provides a dependable record of movements. This integration of object detection with the blockchain and AI can lead to more accurate inventory management, reduce operational costs and improve supply chain transparency.

Industry Transformations

Retail

By combining blockchain and AI retailers can create a more efficient, secure and personalized shopping experience for customers which also enhances supply chain management. This integration can help retailers stay competitive in the rapidly developing digital landscape and meet the demand for transparency and security in the retail field.

The integration of blockchain and AI can update payment processes giving the capability to improve cybersecurity and allow for more efficient inventory management. Smart contracts on the blockchain can automate various retail operations such as – managing supplier agreements and ensuring timely payments.

The combination of blockchain and AI in the retail industry has the potential to improve transparency, customer experience, operational efficiency and trust which has increased the authenticity and proper sourcing of products.

Personalized Recommendations Using Blockchain

Personalized recommendations using blockchain technology can be achieved by combining the power of AI and blockchain to create a more efficient and secure system. With the support of AI algorithms that understand – customer behavior, purchase history and preferences retailers can offer highly custom-made product recommendations. This personalized data can be securely stored on a blockchain that ensures the privacy and security of customer information.

Blockchain can provide a dependable platform for managing customer data where AI continuously learns and adapts to individual preferences which leads to more accurate and relevant recommendations over time. By providing more relevant and valuable experiences to the retailers it can build strong relationships with their customers which will improve the security and privacy of their data.

Streamlined checkout with blockchain

AI-powered object recognition and predictive analytics the retailers can adjust inventory management, anticipate customer demand and ensure that popular items are readily available at checkout.

Blockchain technology can be used to securely store – transaction data, ensuring transparency and security. Smart contracts on the blockchain will have the ability to automate payment processes, loyalty programs and refunds for the checkout experience for both customers and retailers and this improves customer satisfaction.

AI can provide a personalized checkout process by offering custom-made promotions that suggest complementary products and providing efficient customer support. This personalized and efficient checkout experience will lead to improved customer loyalty and higher conversion rates. The checkout process has the potential to improve operational efficiency, enhance customer satisfaction and increase the business growth for retailers.

Banking and Finance

Fraud detection with blockchain

AI and blockchain technology are increasingly being used for fraud detection and machine learning is a subset of AI that is essential for – fraud detection, algorithms and automation to identify and prevent fraudulent activities. AI has improved fraud detection by analyzing historical data identifying patterns of fraudulent activity that led to identity theft and ensuring that only genuine users can access the blockchain.

Integrating blockchain and AI for fraud detection can significantly improve the security and reliability of financial transactions and data. The decentralized and immutable ledger provides a secure and transparent record of transactions which makes it difficult to manipulate data.

The integration of blockchain and AI for fraud detection can lead to more effective and efficient identification of fraudulent activities that can reduce financial losses and enhance trust in transactions.

Technical Challenges

The integration of blockchain and AI presents several technical challenges that need to be faced for successful implementation and one of the challenges is the scalability of both technologies. Blockchain networks often face scalability issues when handling a large number of transactions whereas the AI algorithms require significant computational resources for training. Some of the technical challenges in integrating AI and blockchain technology include:

  • Scalability – Blockchain networks often struggle to handle the increased volume of transactions, leading to bottlenecks and delays which can delay the capabilities of AI.
  • Interoperability – Ensuring that different blockchain networks can communicate and share data effectively is a significant challenge, particularly with legacy systems.
  • Performance – Blockchain technology is complex, and its performance can be affected by factors such as transaction processing speed and capacity.
  • Data Privacy and Security – Ensuring the privacy and security of data used for AI training and analysis in blockchain systems is a critical challenge.
  • Skills Gap – Integrating AI and blockchain requires specialized skills and knowledge, which can be a barrier for organizations.

These technical challenges are important for unlocking the full potential of integrating blockchain and AI which also require collaboration across disciplines to develop efficient, secure and scalable solutions.

Future Outlook

The integration of blockchain and AI has a promising future that can transform various industries and drive innovation. Both technologies continue to develop and the junction is expected to create new opportunities along with new solutions that can create new ways to operate businesses and interact with the customers.

In the future the development of more sophisticated AI algorithms that are specifically designed to control the unique capabilities of blockchain technology and this includes AI systems that can securely analyze and process data. The data are stored on decentralized ledgers which leads to more efficient and transparent decision-making processes.

The combination of blockchain and AI is probable to lead to the emergence of new business models and applications, particularly in areas such as – supply chain management, healthcare, finance and cybersecurity. These innovations may include – enhanced fraud detection systems, personalized customer experiences and transparent data management solutions.

Blockchain and AI have the potential to address pressing societal challenges such as – data privacy, security and ethical AI development. The blockchain is known for its transparency whereas the AI has analytical capabilities due to which the organizations can work towards more responsible and ethical use of data and technology.

Conclusion

The integration of blockchain and AI presents a transformative opportunity across various industries and combining the transparency and security of blockchain with the analytical capabilities of AI businesses can enhance customer experiences, streamline operations and solve critical societal challenges. The potential for personalized recommendations, streamlined checkout processes, fraud detection and improved inventory management showcases the important impact of this integration.

It is important to acknowledge the technical challenges such as – scalability, interoperability and data privacy that need to be addressed for successful implementation. Overcoming these challenges will require collaborative efforts and innovative solutions. The future outlook for blockchain and AI integration is promising which has the potential to drive innovation, create new business models, and get over the societal challenges. We recommended exploring specific use cases for integrating blockchain and AI to invest in skill development and collaboration, conducting pilot projects to test the integration, considering ethical implications and staying informed about the evolving capabilities of these technologies. This approach will help in harnessing the potential of blockchain and AI integration, driving innovation, improving operational efficiency and solving critical challenges.

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AI Regulation Ethical AI

AI Regulation: An Unequivocal Urgency

The pace with which AI has visibly demonstrated its capability is nothing but surreal. No matter the industry that you work in, AI is bound to be part of your work conversation. Subsequently, it has also spilled over to our dining tables. But with the wonders that generative AI has brought to us, it is equally capable of disasters. This is not solely because of the inherent capabilities of the technology itself, since in the past there have been numerous innovations that had comparable capability to affect human life.

However, the adverse ability of the past technologies was largely controlled because state institutions were more or less capable of gauging the significance of its impact on society and thus formulating frameworks to mitigate its risk. But with AI’s extraordinary rapid growth and expansive domain, formulating a regulatory framework presents a huge challenge.

Unprecedented Executive Order

Recognizing this urgency, we witnessed US President Joe Biden sign an executive order (EO or the Order) on Safe, Secure, and Trustworthy Artificial Intelligence (AI) to advance a coordinated, federal governmentwide approach toward the safe and responsible development of AI. In the past there have been executive orders that addressed some aspects of technology, such as IT management, cybersecurity, and critical infrastructure, but they have never focused on a specific technology like AI.

In a similar manner the first AI safety summit was hosted by the UK in Bletchley – the place which was basecamp for second world war codebreakers – Those attending included the US vice-president, Kamala Harris, the European Commission president, Ursula von der Leyen, award-winning computer scientists, executives at all the leading AI companies – and Elon Musk.

Bletchley Summit for AI Regulation

The summit recognised multiple risk, emphasizing particular safety risks arising at the ‘frontier’ of AI, understood as being those highly capable general-purpose AI models, including foundation models, that could perform a wide variety of tasks – as well as relevant specific narrow AI that could exhibit capabilities that cause harm – which match or exceed the capabilities present in today’s most advanced models.

The Bletchley Declaration

As per the Bletchley Declaration, the agenda for addressing frontier AI risk will focus on:

  • Identifying AI safety risks of shared concern, building a shared scientific and evidence-based understanding of these risks, and sustaining that understanding as capabilities continue to increase, in the context of a wider global approach to understanding the impact of AI in our societies.
  • Building respective risk-based policies across our countries (participating countries) to ensure safety in light of such risks, collaborating as appropriate while recognizing our approaches may differ based on national circumstances and applicable legal frameworks. This includes alongside increased transparency by private actors developing frontier AI capabilities, appropriate evaluation metrics, tools for safety testing, and developing relevant public sector capability and scientific research.

The government agencies have set a lofty goal, and they have a history of being unreliable and inefficient. On the other hand, the prompt action is remarkable and motivating. Therefore, stakeholders need to make sure that efforts are focused in the right directions and benefit the general population without obstructing the advancement of technology.

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IT Graduates Panic Over Hiring

As per a survey report approximately 1.1 million students enrolled in CS engineering courses across the country in 2021, and the number has only grown in the past years. The IT industry hires most of these fresh engineering graduates and a fraction of them get a decent placement package. Barring the exceptions from the IITs and a few private institutes, a NIRF report by the Ministry of Education, the average package for an engineering graduate was Rs 4.57 lakh pa.

Harsh Reality

But even this has been in jeopardy with the recent stagnation in hiring by major recruiters in the country. For Q1 2023, the six leading IT services in India – Tata Consultancy Services (TCS), Infosys, HCLTech, Wipro, LTIMindtree, and L&T Technology – witnessed a drastic employee contraction of 18,000 worse than negative 9,000 in the June quarter of 2021 during the pandemic.

According to data from TeamLease, the Indian IT sector will hire 40% fewer freshers as compared to FY23, when they onboard only 2,50,000 engineers. The placement season for the IT industry begins generally in August – September month, but this year they weren’t present on the campuses.

Placements are usually over by November but now it may extend to Q1 2024 due to repeated delays by the major firm.

A Shift in Priorities

An additional trend being seen in the industry according to a report by Business Standard is that the major recruiters are avoiding hiring from private institutes in Tier 2 and Tier 3 cities which have the most engineering students in the country. The standards of the companies have increased in terms of skills and are being pickier in choosing candidates, and interestingly tech startups are the ones which are filling the void left by big companies. But for obvious reasons, they do not pay as well as the big companies.

Tech Startups to the Rescue

The reason for this hiring stagnation and changes in trends is probably because of the reduced or stagnant revenue growth for the IT companies. In 2022, the US accounted for 62% of India’s total IT software and services exports. This itself is enough for us to realize one of the important reasons behind the delayed hiring by IT companies. With inflation still being a major crisis in the US and discretionary spending on the low, Indian IT companies are facing slow growth because of macro headwinds and tech spending being pulled by clients.

A Glimpse of Hope

Leaving aside the short-term despair being faced by the upcoming graduates, we can expect the situation to normalize by Q1 2024 when the activity for the IT industry picks up pace. With Gen-AI and artificial general intelligence being on the rise, the current phase is the perfect opportunity for IT companies to undergo re-structuring and re-training of their employees to build their capacity and most of them have already announced their plans to do so.

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ai business ideas

AI Business Ideas – Detailed Research Report

AI acquisitions remain one of the most common exit paths, especially for earlier-stage companies. Larger tech giants are always on the lookout for innovative new technologies and talent that can accelerate their own roadmaps. Once a startup reaches a certain scale or achieves key technical milestones, they become acquisition targets.

IPOs have also been increasingly popular in recent years as public markets warm to technology. However, IPOs generally require a longer timeframe – 3-5 years is typical to demonstrate consistent growth and profitability. Going public also means ongoing public disclosure requirements.
Special purpose acquisition companies (SPACs) have emerged as an alternative to the traditional IPO. In a SPAC deal, a public shell company acquires the private startup, allowing it to obtain public listing more quickly. However, AI SPAC mergers also come with risks and uncertainty.

Other options include strategic partnerships where technology or IP is licensed rather than the whole company being acquired. Management buyouts may let founders cash out earlier if a larger exit isn’t imminent. In the worst cases, bankruptcy or shutting down remains an “exit” of last resort.
The optimal strategy depends on each startup’s specific situation, goals and investors.

Having alternative exit pathways in mind from the beginning can help navigate the business through different market conditions as well.

Here is a list of ideas that RFC has contributed to:

  1. Acquisitions by larger companies in related sectors often make strategic sense once a startup has demonstrated proof of concept for their technology. This de-risks further development costs for the acquirer. In healthcare, we’ve seen deals like Johnson & Johnson acquiring Momenta Pharmaceuticals, which was developing novel AI tools for disease screening.
  2. IPOs are well-suited for companies that have progressed beyond the earliest stages of R&D and are generating significant customer revenue. This provides access to public capital markets to further scale commercial operations. One medical AI company that went public relatively early is Butterfly Network, which has created portable ultrasound devices and last year raised $300M in its IPO.
  3. Licensing agreements can be an attractive path if a startup wants to focus on its core technology development rather than long-term operations. This allows the IP and research to be leveraged more broadly. In healthcare, Brainomix signed deals licensing its stroke detection algorithms to larger hospital networks to aid diagnosis.

There are several potential exit strategies for AI and technology startups in the healthcare field as they progress from early research to commercialization efforts. Acquisitions by larger companies, IPOs, and licensing deals all represent common paths, allowing startups to realize value from their innovations while larger entities gain access to promising new technologies.

The optimal approach will depend on each individual company’s specific goals, investors and stage of development. With advance planning and flexibility to consider different options as conditions change, startups can help position themselves to successfully navigate changing market dynamics and achieve an attractive exit.

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hopabot main

Hopabot – Comprehensive Technical Report

Hopabot is a chatbot deployment platform that lets developers build all sorts of automated scenarios and chatbots using blockchain tech. One really useful feature is how it lets you create “entities” that bots can be based on. This helps make sure the bots stay consistent and personalized.

Ruskin Felix Consulting LLC helped Hopabot on strategic and technical expertise as we formulated a fully operational technical documents which featured which emphasized and articulated the functionalities of the platform and the logic behind its operations.

Hopabot also gives you tons of tools to make bot building easier – like a simple drag and drop interface. There’s a powerful natural language processor to help bots understand chat. And you can integrate other apps for extra functionality, like payments or customer support. All in all, it aims to help users create engaging bots however they want.

Once you build a bot, Hopabot lets you sell or rent it out on their marketplace too. It works for both businesses and individuals. Companies can use it to build their own bots or hire someone else’s. Individual developers can make bots to sell.

And the marketplace gives everyone access to a whole range of automated solutions. Basically, it’s a great all-in-one platform no matter your skill level or needs!

Here are a few other aspects of Hopabot’s network layer architecture that help enhance security:

  • Encrypted node communication: Data transmitted between nodes is encrypted in transit to prevent snooping or tampering. This protects the integrity of transactions and network data.
  • Firewalls and intrusion detection: Tools like network firewalls monitor traffic and detect anomalous patterns that could indicate malicious activity. This provides visibility into potential security risks.
  • Automated patching: Nodes are configured to regularly install the latest software updates from maintainers. This helps defend against newly discovered vulnerabilities before they can be exploited.
  • Access control lists: Fine-grained ACLs restrict which nodes can initiate connections or perform administrative actions. This limits the impact if a node is compromised.
  • Distributed monitoring: No single point of failure exists for monitoring the network, as nodes all share responsibility. This enhances availability of security tools.

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apple gen ai

Apple’s Increased Investment in Generative AI

Generative AI is advancing rapidly, with pioneering models demonstrating vast potential to automate content creation. Companies like OpenAI, Anthropic and others have taken early leadership with groundbreaking research. Meanwhile, firms like Google, Microsoft and Amazon collectively pour billions into AI yearly and show no signs of slowing investment. These companies have already debuted powerful generative products, putting pressure on Apple.

Based on our analysis of the generative AI field and conversations with leading researchers, we estimate Apple will need to invest around $1-2 billion annually to effectively compete in this critical area over the next 5 years. While this represents a sizeable commitment, it is necessary to avoid losing ground to competitors aggressively funding generative AI development like Google, Microsoft and Amazon. These firms already collectively pour billions into AI each year and show no signs of slowing investment.

Our data suggests that in 2023 and 2024, Apple will buy between 2,000 and 3,000 and 18,000 to 20,000 AI servers. In 2023 and 2024, it will account for around 1.3% and 5% of global AI server shipments, respectively.

Apple’s Position

While Apple uses AI across its products, it has yet to launch a generative AI system or application. Internally developed models like Apple GPT and Ajax have not been integrated into products. Apple lags behind competitors in generative AI research and commercialization. Without dedicating proper resources, Apple risks losing the ability to drive innovation and capitalize on emerging opportunities in this critical field.

Nvidia’s HGX H100 8-GPU, built for generative AI training and inference, seems to be the most popular specification this year, so it’s likely that’s what Apple is buying for its AI servers. Some 4Q24 shipments may additionally include an upgrade to the B100 solution.

The average cost of an HGX H100 8-GPU server is $250,000. That’s why experts predict Apple will shell out at least $620 million on artificial intelligence (AI) servers in 2023, and another $4.75 billion the following year.

Generative models are rapidly growing in scale and capabilities. Training increasingly powerful models requires vast computing resources that come at a high cost. To develop world-class generative research and integrate related technologies into its products on a timeline similar to peers, Apple will need dedicated funding on the scale mentioned above. Anything less risks ceding leadership in a domain that may define the technology industry’s future.

Funding Needs

Our study into the topic of generative AI and our conversations with experts have led us to conclude that Apple will need to invest between $1 to $2 billion each year over the next five years. This scale of funding is necessary to develop world-class generative research, hire top talent, acquire capabilities, and integrate related technologies on par with industry leaders. Sustained investment below this level could severely limit Apple’s competitiveness in generative AI going forward.

Of course, the precise figure could vary based on strategic priorities and technological breakthroughs. But make no mistake – without serious commitment to generative AI in the billions, Apple’s ability to drive innovation in this sphere and capitalize on emerging opportunities will be limited. As with other transformative technologies, sustained investment is key to gaining a long-term competitive edge.

Recommendation

Our advice would be that Apple and other firms to carefully assess generative AI’s potential impacts and allocate commensurate resources to ensure they can actively shape, rather than merely react to, the changes to come. The winners of tomorrow will be those investing boldly in advanced AI today.

As a leading technology company, Apple recognizes the importance of artificial intelligence, particularly generative AI, in driving future innovation. However, substantial investment will be required for Apple to effectively compete in this critical area against peers aggressively funding AI development. In this report, we analyze Apple’s position in generative AI and estimate the level of funding needed over the next 5 years to close the gap with competitors.

We advise Apple to carefully assess generative AI’s impacts and allocate commensurate resources to shape emerging changes. The winners in technology industries are those investing boldly in advanced AI. Apple must commit serious funding in the billions for generative AI to remain competitive and a leader in driving innovation. Without such commitment, ceding ground to better-funded peers in this pivotal domain will be difficult to avoid.

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Quantum Computing and its Commercialization

Quantum computing is rapidly advancing from theoretical research toward practical business applications. Where it was once confined to laboratories, quantum technologies have reached an inflection point of readiness that is demanding attention from both technology leaders and mainstream enterprises.

As the technology reaches an inflection point of viability within the next two to five years according to many estimates, businesses must gain a working knowledge of quantum computing’s opportunities and limitations. Those preparing now by experimenting with available cloud-based resources and developing quantum roadmaps will find themselves well-positioned for the coming wave of innovation.

Materials Development Through Quantum Simulation

Daimler leveraged IBM’s quantum computer to model molecular structures, simulating different atomic configurations to design more efficient battery materials. This showed quantum’s potential to revolutionize materials science by testing hypotheses that would take classical computers millennia. Other work simulates organic photovoltaic cells and catalysts.

While challenges certainly remain, the field has made tremendous strides in the last five years alone. Quantum volume – a measure of processing capability – has increased exponentially on hardware from IBM, Rigetti, IonQ and other vendors. Meanwhile, software tools are maturing to help programmers without quantum physics backgrounds develop and test algorithms.

Financial Portfolio Optimization with Quantum Machine Learning

JPMorgan partnered with IonQ to test portfolio allocation algorithms on a quantum processor. Though in early stages, quantum machine learning models could one day optimize trillion-dollar investment portfolios to outperform classical AI. Several startups are also developing quantum risk analysis and other financial applications.

Quantum technologies have progressed significantly in recent years, attracting record levels of investment from both private enterprises and public institutions. As startups in the field become more established, venture capital funding reached new highs of $2.35 billion in 2022 according to McKinsey’s Quantum Technology Monitor.

Quantum Artificial Intelligence to Design New Medicines

Researchers at GlaxoSmithKline, Google and University of Southern California used quantum processors to simulate molecular docking and design potential drug candidates. Quantum AI may discover new medicines by screening billions of molecular structures far more efficiently than classical computers. The technique could transform drug discovery.

Looking ahead, quantum will integrate into mainstream IT environments much like cloud technologies before it. Major consulting firms including BCG and McKinsey have launched dedicated quantum computing practices to help clients strategize integration approaches. Meanwhile, tech giants from Amazon to Microsoft are investing heavily in quantum hardware and services to capture a leadership position in this next generation of processing.

This influx of capital is being driven by tangible signs that quantum computing is maturing from theoretical research into viable business solutions. Hardware performance continues to grow exponentially, with the number of quantum bits (qubits) doubling each year on average. Software is also advancing to simplify programming for non-physicists.

Solving Supply Chain Optimization Problems

Logistics heavyweight DHL explored using quantum annealers from D-Wave to tackle routing, inventory and delivery scheduling. Complex supply chain optimization problems involving thousands of variables are well-suited for quantum approaches. Successful tests could see broader adoption across transportation and manufacturing.

Moving forward, quantum technologies are on track to become integrated into mainstream IT environments within the next five years. Tech giants and consulting firms already offer dedicated quantum services, recognizing the opportunity in shaping this next generation of computing.

While challenges around error correction and scaling remain, the field has reached an inflection point where businesses must start preparing for quantum’s disruptive impact. Those who gain expertise now and develop quantum roadmaps will find themselves well-positioned to capture competitive advantages as innovation accelerates. With continued progress, quantum applications may revolutionize industries from automotive to finance in the coming decade.

While still in early stages, these examples show how quantum is beginning to solve problems beyond traditional computing’s reach. As the technology matures, its full capabilities for fields from energy to healthcare will start to emerge. Commercial integration will ramp up alongside hardware improvements in error correction and qubit scaling. The next decade will likely see quantum achieve critical mass and begin transforming major industries.

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key drivers of indias digital boom

Digitization Wave- A Key Driver of India

India is poised to become a global digital leader, riding on the back of rapid digitization across sectors supported by various government initiatives. With a population of over 1.3 billion and more than 650 million internet users, the size and growth of India’s digital economy presents a trillion dollar opportunity.

As per reports, India’s digital economy is projected to reach $1 trillion by 2025 driven by widespread smartphone and internet penetration. The government aims to digitally empower every citizen through programs like Digital India, boosting e-governance, digital payments, online education and telemedicine. BharatNet is creating digital infrastructure in rural areas while initiatives like Startup India are fostering innovation and digitization.

Transformation of Digital India

As India’s Digital Economy prepares to realise its $1T value potential, a number of factors will push this digitization transformation:

  1. Ubiquitous Digital Consumption: As India’s under-35 population continues to grow and disposable incomes rise, more and more consumption will shift online, boosting the value potential of digitally native and digitally enabled enterprises. A surge in online spending has also been seen due to digitization.
  2. New Business Opportunities: Indian entrepreneurs will continue to innovate business models that fulfil particularly Indian requirements, tapping on infrastructure such as WhatsApp and other social media platforms, leading to an upward curve in digitization.
  3. Public Market Hunger: The investment ecosystem is seeing robust public investor appetite, as seen by the first IPO of an Indian unicorn, Zomato, which was 38 times oversubscribed on listing day, resulting in a valuation of over $13 billion. In addition, the $1 billion initial public offering (IPO) of Freshworks on the NASDAQ is a clear signal of the capacity of Indian enterprises to take the lead on global platforms for digitization.
  4. Strong Private Market Presence: Furthermore, we anticipate that out of the 250M firms already valued at > $100M, approximately 10052 new unicorns will be established in the next 5 to 7 years, helped by the growing interest of global financial investors. This further pushes the digitization process. To benefit on this wealth creation potential, investors will require a combination of extensive networks, local on-ground presence, technical competence and multi-cycle/stage investing experience.

The IT/Business Process Management sector already contributes over 7% to India’s GDP and employs millions. However, the real transformation is occurring in sectors like e-commerce, edtech, fintech, healthcare and agriculture which are being disrupted through technology. Major global tech companies have expanded operations in India to tap the market. Indian startups are also at the forefront of driving innovation, receiving over $73 billion in funding since 2016. The amounts that are disbursed after linking of Aadhar with under-privileged individuals showed an upsurge after the digitization of various e-portals.

E-commerce is a $200 billion opportunity by 2040 with digital payments growing exponentially. The pandemic accelerated digitization adoption – grocery, pharmacy and education saw 4-5x growth. Fintech is revolutionizing banking, insurance and wealth management through offerings like UPI, digital loans and robo-advisory. Edtech and online learning saw 10x growth with the shift to virtual classrooms. Telemedicine and digital health records are improving access to quality care.

5G rollout, blockchain, AI/ML, IoT, cloud computing and data analytics present new avenues in the digitization process. Emerging areas like virtual reality/augmented reality, robotics, drones and cleantech also offer prospects. India’s talent pool of engineers and developers is a major strength to develop these technologies. Partnerships with leading global companies will aid transfer of knowledge.

To fully realize this opportunity, India needs to focus on aspects like data privacy, infrastructure development, skilling workforce for digital jobs and fostering entrepreneurship which will in turn help in the growth of digitization. Continued policy support can help establish India as a global digital powerhouse.

Key enablers of India’s digital success and how they are valued:

Affordable smartphones:

  • India is the second largest smartphone market in the world with over 750 million users. This was made possible by the availability of affordable smartphones under $150 from manufacturers like Xiaomi, Samsung, Vivo etc.
  • Cheap data plans have also boosted adoption, with 1GB of mobile data costing around $0.25 on average in India.
  • Smartphones account for over 90% of total internet usage in India. This widespread availability of low-cost smartphones is valued at over $50 billion and has been instrumental in introducing hundreds of millions to digital services.

Digital payments:

  • India saw a spike in digital payments during the pandemic, growing from $59 billion in 2019 to $3 trillion in 2021.
  • UPI processed over 5 billion transactions worth over $1 trillion in FY23 alone. Major payment platforms like Paytm, PhonePe and Google Pay are also hugely popular.
  • Digital payments have boosted e-commerce by providing safe, convenient options for both buyers and sellers. They also encourage financial inclusion by allowing access to banking services even in remote areas. This cashless ecosystem is valued at over $500 billion currently.

Digital infrastructure:

  • Initiatives like BharatNet have laid over 1.5 million km of optical fibre, connecting over 250,000 panchayats digitally.
  • Digital India program aims to provide broadband access to every citizen. Over 1 billion Indians now have access to high-speed broadband internet.
  • Public WiFi projects under Digital India have created over 10,000 hotspots across India. This expanding digital infrastructure is valued at over $50 billion and helps connect both urban and rural populations online.

India’s rapid transition to a digital-first economy

India is transitioning from a cash-dominated to a digital-first economy at a rapid pace. The pandemic accelerated digitization shift as more citizens adopted digital services for work, education, entertainment and payments out of necessity. Sectors like e-commerce, fintech, edtech saw 4-5x growth. This massive digital adoption will allow India to leapfrog stages of development and establish itself as a global digital powerhouse.

How India and China benefited from their large populations

Both India and China had a key advantage – huge internal markets provided by their large populations. This allowed digital entrepreneurs in these countries to focus on serving domestic demand first, achieving scale. They did not need to look abroad initially for users and customers. Digitization of multiple services will help foster good relations with neighboring countries.

This large captive market acted as an incentive for private companies and the government to invest heavily in digital infrastructure and services. It also attracted global tech giants to prioritize these markets.

How India and China have “leapfrogged” the West

India and China largely skipped establishing traditional landline telephone networks and desktop computer markets. Instead, they moved directly to widespread adoption of more advanced mobile phones and internet on phones.

Mobile phones provided an easy way for their large populations to access the internet and digital services anytime, anywhere. This helped digital and mobile apps flourish in these countries before the West fully transitioned to smartphones, leading the path toward digitization.

Younger populations more receptive to new technologies

The young demographics of India and China made their populations naturally more receptive to new technologies compared to older Western nations. Students and young professionals drove digital adoption through their enthusiasm for the latest apps and gadgets.

This early and rapid adoption of digital technologies among their youth helped India and China develop very vibrant digital ecosystems in a much shorter time frame than the multi-decade transitions seen in the West.

India’s trillion dollar digital economy presents massive investment and partnership opportunities for global digitization and businesses. As a financial consulting firm, we recommend our clients strategize early entry to tap into India’s growing consumer base and talent pool. Investing in digital infrastructure projects and partnering with Indian startups will help gain first-mover advantage in this rapidly transforming market. With continued policy support, India is well positioned to emerge as one of the top global digital economies, delivering high returns for early investors.

Digitization Wave- A Key Driver of India Read More »

Regulating AI Platforms

Artificial Intelligence Platforms’ Regulation

Regulatory Frameworks for Artificial Intelligence Risk Mitigation

Public concern about emerging technologies and their implied risk has been the key focus for years due to the unsupervised use of personal data. With the recent upsurge of Generative Artificial Intelligence (GenAI) including Large Language Models (LLM) and organizations embedding artificial intelligence in various products and processes, the attention of the masses and regulators has been shifting towards the potential for biased decisions by algorithms.

The recent headlines have been marked by artificial intelligence systems producing biased results. One well-known example is Apple’s credit card algorithm, which has been accused of discriminating against women, triggering an investigation by New York’s Department of Financial Services.

Having said that regulators, legislators, and standard setters are now starting to develop frameworks to mitigate the risk while maximizing the optimal use of AI for human mankind.

Building a Collaborative Approach

Recognizing that each jurisdiction has taken a different regulatory approach, the fundamentals on which detailed regulations on artificial intelligence can be built are discussed below:

  • Risk-Centric Approach: Regulations should be tailored to artificial intelligence’s perceived risks, proportionally matching them to compliance obligations with factors like privacy, non-discrimination, transparency, and security.
  • Guiding Principles: AI regulations should be aligned with the Organization of Economic Cooperation and Development (OECD) endorsed principles, emphasizing human rights, sustainability, transparency, and risk management.
  • Versatility in Regulation: Jurisdictions recognize the need for both broad, sector-independent artificial intelligence rules and specialized regulations catering to specific industries.
  • Harmonized Policy: Development of AI-related rules alongside digital policy. Priority topics like cybersecurity, data privacy, and intellectual property protection should be addressed with the EU leading in comprehensive policymaking.
  • Private Sector Collaborations: Ensuring the regulatory tools facilitate private sector collaboration with policymakers addressing the ethical use of artificial intelligence, and high-risk AI innovations that require closer oversight.

Corporate Strategies for Navigating the Evolving AI Regulatory Landscape

With regulators and standard setters, private organizations also play a crucial role in streamlining the rules and regulations for artificial intelligence platforms. Based on the industry trends we have discussed a few common practices that can be implemented by companies to stay relevant in the rapidly evolving AI regulatory landscape:

  • Understanding AI Regulations: Organizations would need to align the regulations issued by regulatory authorities with their internal AI policies, the market in which they operate, and other associated supervisory standards.
  • Strengthening Governance and Risk Management: Establishing clear and robust governance and risk management structures with regulatory alliances can bridge a gap between companies and standard setters. Additionally, actively engaging in conversations with public sector officials and other stakeholders can be helpful for both companies as well as policymakers.

As the growing reliance on artificial intelligence significantly increases the strategic risks businesses face, companies need to take an active role in writing a rulebook for algorithms. Unless all companies including those not directly involved in AI development engage early with these challenges, the businesses would therein face backlashes resulting in a dip in their business profits undermining the true potential AI could render to the consumers and society.

Artificial Intelligence Platforms’ Regulation Read More »

gateway to metaverse gaming

Gateway to Metaverse Gaming

Metaverse – An Emerging Universe

Metaverse, a concept named by now “Meta” previously known as Facebook. The term metaverse refers to the concept of three-dimensional virtual spaces put together to form a universe in itself. It involves a combination of multiple platforms that allow users to socialize, game, meet and work in a three-dimensional space.

Metaverse, powered by Augmented Reality (AR) is gaining traction in various domains. The video gaming industry is said to be in its clooney years as it experiences major transformational shift due to the emergence of metaverse. Amid the rapid growth in the gaming industry post COVID-19 outbreak its basic drivers are still the fundamentals of the industry- faster processors, improving graphics and enhancement of overall gaming experience worldwide.

In addition, the advancement in global communication networks will accelerate the uptake of cloud-based games creating entirely new ways for users to interact and socialize while driving revenue for the gaming companies.  

According to a survey by Amsterdam-based industry tracker Newzoo, the worldwide games market is projected to earn about $188 billion in sales in 2023, up 2.6 percent from this year.

The Metaverse Gaming Impact, Explained!

With the concept of a fictional universe becoming reality there is a significant upsurge with the number of early adopting gaming companies experimenting with a metaverse presence. For instance- the widely played Minecraft and Fortnite games, as well as the popular Roblox game platform, have incorporated many aspects of the metaverse, including virtual worlds where players meet to play games and use social features such as in-game chats.

As the gaming industry matures, the metaverse will continue to incorporate various technologies, such as VR, AR, and 3D functionality. Tim Stuart, CFO of Microsoft’s Xbox Unit stated, “Within the gaming space, competition for engagement makes our business grow. It creates innovation and new ideas. This market is growing because there are new entrants, there are new game players, and there is a flow of new content unlike anything we’ve seen in the past.”

It is observed that an estimated 2.9 billion people – more than one out of every three people on the planet played a video game in 2021, when global revenue for the industry exceeded $193 billion. In addition, from 2016 to 2021, gaming grew at a compound annual growth rate of 15.6%

With customer expectations rising dramatically, a key pillar of success for the gaming companies will be continuous innovation and product differentiation. While companies across every sector are still imagining business possibilities the metaverse offers, gaming executives already see growth potential and have a positive outlook for this industry in the near future. By 2025, the global gaming market is predicted to be worth $211 billion, with mobile gaming accounting for $116 billion of that.

Gateway to Metaverse Gaming Read More »

intangible assets and innovative tech

Intangible Assets & Innovative Tech

Understanding Intangible Assets

Intangible assets are assets that have no physical presence but accrue their value over a period. Generally classified as long-term assets, Intangible assets help companies by performing operations in a unique manner thereby giving them a competitive edge. The main types of intangible assets are Intellectual properties (Trade Secrets, Patents, Trademarks, and Copyrights), licensing, Customer lists, R&D, brand equity, and goodwill.

Businesses can have an intangible value that is not reflected in their physical assets (shown in the financial statements of the company) but rather in their brand reputation. The distinctive features that make a business stand out from its competitors are part of its intangible value. We have gathered the most valuable brands in the world and presented them below:

An interesting fact to note is that the technology industry dominates the list of the most valuable brands in the world, with half of the top 10 spots. This indicates the significant impact that technology has on our daily lives.

Valuation of Intangibles in the Technology Sector

In the emerging knowledge-intensive and globalizing economy, there is an increasing trend towards the valuation of intangibles along with tangibles to assess the intrinsic worth of an organization more realistically on a long-term basis, particularly in the emerging technology sector.

Simply stated the emerging technology sector comprises the following intangible assets:

  • Software: A set of instructions or programs that can be developed or acquired by businesses and can be protected by copyright and patent.
  • Databases: Databases are structured repositories of information like customer, product, and transaction data, potentially safeguarded by trade secrets and contractual confidentiality agreements.
  • License Agreements: License agreements are contracts that authorize the use of intangible assets, such as software, databases, patents, or trademarks, specifying terms like duration, scope, fees, and royalties, serving as a source of revenue or cost for businesses, depending on their role as a licensor or licensee.
  • Patent Technology: Patent technology refers to innovation protected by exclusive rights granted by intellectual property offices, providing businesses with a competitive edge by prohibiting unauthorized use or replication.

Methods of Valuation for Intangibles

To arrive at a “fair” value for a specific intangible, the valuation methodologies are classified under the following three categories:

  • Cost Approach: This approach establishes the present replacement cost of an intangible asset. It serves as a valuable benchmark, especially for easily replicable assets. However, it may not always align with actual market valuations, as it predominantly reflects historical costs.
  • Market Approach: This method assesses the worth of intangible assets by analyzing prices from real transactions. Utilizing ratios like revenue, it derives market multiples. This approach necessitates a comprehensive understanding of transaction specifics and demands benchmarking against factors such as competitive positioning and future growth potential.
  • Income Approach: Regarded as the most precise method, the Income Approach determines an intangible asset’s value based on its future economic returns. This evaluation involves quantifying the asset’s impact on cash flows when integrated with other assets. It requires a thorough examination of a business’s financials, organizational structure, operational processes, identification of value drivers, and the quantification of their influence.

However, not even one method of valuation could meet the requirements under all situations. A basket of techniques needs to be used to arrive at a fairly reliable estimate. The most appropriate strategy so far appears to be to compute the value as per the various methods and realize proceeds based on the “best value”, yielding the maximum proceeds, which is very subjective.

Intangible Assets & Innovative Tech Read More »

robotics in healthcare

Robotics in the Application of Healthcare

The healthcare industry has rapidly adopted robotics to improve patient care, improve surgical procedures, and streamline administrative tasks. Robotics provides many benefits, including increased accuracy, reduced human error, and increased efficiency.

Medical Robotics Market size was valued at USD 12.5 billion in 2022. The Medical Robotics Market industry is expected to grow from USD 14.4 billion in 2023 to USD 44.4 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 17.16% during the forecast period (2023-2030).

In 2022, North America held a sizable market share for healthcare assistive robotics technology, and it is anticipated that it would continue to dominate over the forecast period. The primary drivers of the market’s expansion are the increasing prevalence of bone injuries, increased healthcare spending, and greater public awareness of the creative and cutting-edge uses of robotics.

On the other hand, Asia-Pacific is anticipated to experience the fastest growth throughout the anticipated period for the market for healthcare assistive robots. The medical equipment industry’s presence in the area and the rising purchasing power of populous nations like China and India are both responsible for the market expansion in this area. Additionally, the robotics market is expanding due to the increase in R&D activities for the creation of new healthcare assistance devices. 

Types of Healthcare Robots

Today healthcare facilities have access to a range of medical robots designed to perform specific functions. The major ones include-

Applications of Robots in Healthcare

By application below are the key robots in the market in terms of its market share

Neurosurgeries

The dexterity, precision, and enhanced 3D visualization offered by robotics and its platforms allow neurosurgeons to perform minimally invasive procedures with improved accuracy. Robotic stereotactic procedures resulted in fewer complications compared to frame-based approaches for conditions like Parkinson’s disease. Robotics is also enabling new procedures like deep brain stimulation for neurological disorders. The ability to plan and guide intricate procedures is propelling the adoption of robotics in neuro-oncology and other areas. For example, ROSA system developed by Zimmer Biomet.

  • Laparoscopy

The laparoscopic application segment accounted for over 25% of the medical robotics market share and is expected to exhibit a CAGR of 21% till 2030. Robotic systems provide surgeons with improved ergonomics, 3D visualization, and enhanced dexterity compared to traditional laparoscopy. This enables complex procedures to be performed with smaller incisions, leading to reduced post-operative pain and shorter hospital stays for patients. One of the most widely used robotic systems for laparoscopy is the da Vinci system, developed by Intuitive Surgical.

  • Orthopaedic Surgeries

Robotics and its technologies assist surgeons in achieving optimal implant placement and alignment, improving outcomes for procedures like knee replacements. Robotic-assisted total knee arthroplasty led to better post-op function scores compared to conventional surgery and promises advantages like reduced length of stay and readmission rates. Ongoing R&D aims to expand the use of robotics to other areas like spine, trauma, and joint repair surgeries. NAVIO system, developed by Smith & Nephew is an example of this type of robot.

  • Pharmacy Applications

Robotics and its solutions can accurately count pills, label prescriptions, and organize inventory – reducing errors, improving efficiency and freeing up pharmacists for patient-centric roles. Robotic dispensing systems led to a significant decrease in dispensing errors in an academic medical centre. TUG system developed by Aethon has been used for deliveries worldwide.

Key Players

In this rapidly evolving and expanding field some of the main players in the market and their recent development are provided below.

  • iRobot Corporation (U.S.) is a pioneer and leader in consumer robotics, with more than 40 million home robots sold worldwide. The company also develops and provides software and services to energy, water, and communications industries. Some of the recent developments of iRobot are:
    • In May 2019, iRobot acquired Toronto-based Sigma Systems, which provides a variety of OSS and analytics systems to network operators of all types.
    • In January 2023, iRobot unveiled its next generation technology and participated in meetings to support the strategic review process alongside the 41st Annual J.P. Morgan Healthcare Conference. 
  • Titan Medical Inc. (Canada) is a medical device company focused on single access robotic-assisted surgery (RAS). The company’s flagship product is the Enos™ robotic single access surgical system, which is designed to provide a surgical experience that imitates real-life movements that surgeons demand and includes multi-articulating instruments that allow surgeons an increased range of motion in a confined space. Some of the recent developments of Titan Medical are:
    • In February 2022, Titan Medical completed the final milestone under the development and license agreement with Medtronic plc, the world’s leading medical technology company. The milestone involved the development and delivery of novel robotic surgical technologies for use by Medtronic in its robotic platforms.
    • In June 2023, Titan Medical signed an asset purchase and license agreement with Medtronic, under which Titan Medical sold certain robotic intellectual property assets to Medtronic and granted Medtronic a worldwide, non-exclusive license to use certain other robotic intellectual property assets in return for $150 million in upfront cash and potential future milestone payments.
    • In January 2023, Titan Medical announced the unveiling of its next generation technology and participation in meetings to support the strategic review process. The company also shared a video highlighting its latest innovation in robotic-assisted surgery.
  • Stryker Corporation (U.S.) offers a diverse array of innovative products and services in orthopaedics, medical and surgical, neurotechnology, and spine. The company is committed to improving patient and hospital outcomes through its products, services, and solutions. Some of the recent developments of Stryker are:
    • In November 2019, Stryker completed the acquisition of Wright Medical Group N.V., a global medical device company specializing in extremities and biologics. The acquisition enhanced Stryker’s position and portfolio in the fast-growing segments of orthopaedics, such as upper extremities, lower extremities, and biologics.
    • In January 2020, Stryker acquired OrthoSensor, Inc., a leader in the digital evolution of musculoskeletal care and sensor technology for total joint replacement. The acquisition added OrthoSensor’s advancements in sensor technology, data analytics, and artificial intelligence to Stryker’s digital surgery platform.
  • Intuitive Surgical (U.S.) with more than 10 million procedures performed using its da Vinci surgical systems. The company also develops and provides other innovative technologies, such as the Ion endoluminal system for lung biopsy, the Iris augmented reality system for surgical planning and visualization, and the SureForm stapler for advanced tissue management. Some of the recent developments of Intuitive Surgical are:
    • In April 2020, Intuitive received FDA clearance of its da Vinci SP surgical system for urologic surgical procedures that are appropriate for a single port approach. The da Vinci SP system provides surgeons with robotic-assisted technology designed for deep and narrow access to tissue in the body.
    • In July 2020, Intuitive launched its new da Vinci Xi/X integrated table motion in collaboration with Trumpf Medical, a leading supplier of medical equipment and solutions. The integrated table motion enables the da Vinci Xi/X surgical systems and the Trumpf Medical TruSystem 7000dV table to communicate and move in sync during robotic-assisted surgery.
  • Renishaw plc (U.K.) is a leading global provider of engineering and scientific technology solutions, with expertise in precision measurement, additive manufacturing, motion control, healthcare, and spectroscopy. The company offers a range of products and services, such as probes, sensors, gauges, encoders, scanners, printers, robots, software, and calibration. Some of their recent developments of are:
    • In January 2021, Renishaw launched its new RFP fringe probe for the REVO 5-axis measurement system on co-ordinate measuring machines (CMMs). The RFP probe is designed to deliver non-contact structured light inspection of complex surfaces and features, such as freeform shapes, splines, and gear teeth.

The use of robotic systems in surgeries presents significant opportunities for major players in the medical robots market in developing countries, particularly in the Asia Pacific region. With lower-cost options for radiation treatment and fewer regulatory restrictions, market participants are increasingly focusing on emerging markets. The market share of medical robots is expected to rise rapidly due to increased healthcare spending, surgical procedures, and the expansion of key players especially in developing regions.

Robotics in the Application of Healthcare Read More »

generative ai blog

Generative AI

Introduction

Generative AI comes under the domain of artificial intelligence which can engender new content based on previously amassed information, including text, images, audio, video, and more. It can create new and realistic content that reflects the traits of the training data but does not reiterate it, in contrast to traditional AI, which analyses or classes data.

The way businesses operate, innovate, and compete in the digital era may transform as a result of generative AI. It can facilitate more affordable content creation, improve customer service, boost worker efficiency, and open the door to new business models and applications. This newsletter attempts to take a stride on understanding and having a good knowledge on generative AI.

Recent News

Generative AI is a rapidly evolving field that has the potential to transform various domains and industries with its creative and innovative applications. From generating realistic images and text to enhancing existing tools and increasing choices, generative AI is making big strides every day. Here are some of the recent news on generative AI:

  • Amazon has announced a strategic investment of $4 billion in Anthropic, an AI startup, marking a significant move to enhance its presence in generative artificial intelligence. This partnership not only involves a substantial financial commitment but also provides Anthropic with access to Amazon’s formidable computing power.
  • Infosys and Microsoft have partnered to develop and deploy generative AI solutions for businesses. The companies will work together to develop new generative AI models and tools, and to integrate generative AI into Microsoft’s cloud platform. This partnership could accelerate the adoption of generative AI by businesses of all sizes. It could also lead to the development of new and innovative solutions.
  • Auctoria is a generative AI tech that can create a range of different model types for video games. It was created to support game development professionals in their work. One of the platform’s features attempts to generate entire 3D game levels, complete with pathways for players to explore, while another converts uploaded images and textures of walls, floors and columns into 3D equivalents of that artwork.
  • SAP has developed its own generative AI assistant, called CoPilot, that can help businesses automate tasks, improve productivity, and make better decisions. It can be used to generate reports, create presentations, write emails, analyse data, and identify trends. CoPilot could help businesses to save time and money, and to make better decisions. It could also lead to the creation of new jobs and industries.
  • AppyHigh has launched a bundle of generative AI apps that can be used to create different types of creative content. It includes apps for generating blog posts, social media content, product descriptions, and marketing campaigns. This app bundle could make it easier for businesses to create high-quality creative content. It could also lead to the development of new and innovative types of creative content.
  • Generative AI was used for the movie Everything Everywhere All at Once, which was released in 2022.  The movie used generative AI to create some of the visual effects, backgrounds and to create some of the dialogue and storylines.

Some of the possible applications of generative AI in different industries are:

  • Generative AI can support designers and engineers in devising new and innovative products, such as logos, websites, apps, games, furniture, and vehicles.
  • It can enhance diagnosis, treatment, and prevention of diseases, as well as produce syntheticdata for research and training purposes.
  • In the manufacturing, automotive, aerospace and defence industries, generative design can create designs optimized to meet specific goals and constraints, such as performance, materials and manufacturing methods.
  • Generative AI can assist fashion designers and retailers in creating new and trendy clothing, accessories, and styles, as well as generate realistic and diverse models and images for displaying their products.

The generative AI market is expected to grow rapidly in the coming years, driven by the incrementing demand for content creation, the availability of large-scale data, the advancement of AI techniques, and the emergence of cloud-based platforms and services.

According to a report by Statista , the global generative AI market size is projected to reach $44.89 billion in 2023, growing at a compound annual growth rate (CAGR) of 24.40% from 2023 to 2030 achieving in a market volume of $207 billion by 2030.

From our market analysis, we were able to postulate the following:

The rising need for synthetic data to train AI models, especially in domains where data is scarce, sensitive, or extravagant to accumulate, such as healthcare, finance, and security.

The growing adoption of natural language processing (NLP) and computer vision applications, such as chatbots, virtual assistants, image and video generation, and face and voice synthesis, across sundry industries, such as retail, media, entertainment, and education.

The increasing investment and research in generative AI by leading technology companies, such as Google, Microsoft, Amazon, Facebook, IBM, and Salesforce, as well as academic institutions, such as MIT, Stanford, and Oxford, and open-source communities, such as OpenAI and TensorFlow. The emergence of cloud-based generative AI platforms and services, such as ChatGPT, DALL-E, StabilityAI, and Midjourney, that offer easy access, scalability, and affordability to users, without requiring specialized hardware or software.

The above table shows the comparison of different generative AI models from some of the early providers in terms of their modalities. Microsoft have its various models such as VALL-E for speech synthesis and editing audio clips, RODIN Diffusion that sculpts 3-D avatars using diffusion, GODIVA generates videos from text and MoLeR, a generative model of molecular graphs that can create new molecules based on a given scaffold and a set of structural motifs. generative model of molecular graphs that can create new molecules based on a given scaffold and a set of structural motifs.

While generative AI will likely affect most business functions over the longer term, our research suggests that information technology, marketing and sales, customer service, and product development are most ripe for the first wave of applications.

  • Information technology: Generative AI can help teams write code and documentation. Already, automated coders on the market have improved developer productivity by more than 50 percent, helping to accelerate software development.
  • Marketing and sales: Teams can use generative AI applications to create content for customer outreach. Within two years, 30 percent of all outbound marketing messages are expected to be developed with the assistance of generative AI systems.
  • Customer service: Natural-sounding, personalized chatbots and virtual assistants can handle customer inquiries, recommend swift resolution, and guide customers to the information they need. Companies such as Salesforce, Dialpad, and Ada have already announced offerings in this area.
  • Product development: Companies can use generative AI to rapidly prototype product designs. Life sciences companies, for instance, have already started to explore the use of generative AI to help generate sequences of amino acids and DNA nucleotides to shorten the drug design phase from months to weeks.

In the near term, some industries can leverage these applications to greater effect than others. The media and entertainment industry can become more efficient by using generative AI to produce unique content and rapidly develop ideas for new content and visual effects for video games, music, movie story lines, and news articles. Banking, consumer, telecommunications, life sciences, and technology companies are expected to experience outsize operational efficiencies given their considerable investments in IT, customer service, marketing and sales, and product development.

Traditional Role Played by Gen AI

The creative business is undergoing a radical transformation as generative AI, a form of artificial intelligence that can create original and realistic content, is becoming more accessible and powerful. It can produce diverse outputs, such as images, video, music, speech, text, software code and product designs, by learning from existing data and applying complex algorithms. It has been growing at an alarming rate, with new tools and platforms emerging every day.

According to an article, the Writers Guild of America (WGA), which speaks for approximately 11,500 writers in the film and television sector, arrived at an initial three-year agreement with prominent studios on the previous Sunday. Nevertheless, the deal still necessitates endorsement from the union’s leadership and its members.

However, generative AI also poses a threat to the traditional roles and processes of creative businesses. In fact, one of the main reasons for the recent Hollywood writers’ strike, which lasted for nearly five months and disrupted the film and television industry, was the fear of it taking over their jobs. The writers demanded better compensation and recognition for their work, as well as more control over the use of their intellectual property by studios and streaming services that rely on them to produce content.

Generative AI is not only affecting the writers, but also a variety of other facets encompassing the creative domain. For instance, digital art is being revolutionized by generative AI tools such as DALL-E, which can generate images from text descriptions, or Midjourney, which can create realistic portraits of fictional characters. Music production is also being influenced by generative AI platforms such as Bard, which can compose original songs based on user input, or DeepMind, which can synthesize realistic voices and instruments. Video editing, dubbing, animation, gaming and many more creative fields are also being impacted by technologies. Generative AI was used in making the 2022, Oscar winning film, “Everything Everywhere All at Once”, and we know how that turned out.

What does this mean for the future of the creative business?

While some may see generative AI as a threat, others may see it as an opportunity. Generative AI is not here to replace the creative team, but rather to augment and enhance their capabilities. Generative AI can help the creative team to save time, reduce costs, improve quality, generate ideas, explore possibilities and experiment with new formats. The creative team can also leverage generative AI to reach new audiences, customize content and personalize experiences.

The creative business is facing a disruptive force in the form of generative AI. However, disruption can also lead to innovation and growth. The key is to embrace generative AI as a partner rather than a competitor, and to use it as a tool rather than a replacement. By doing so, the creative business can unlock new potential and create value for themselves and their customers.

Generative AI Read More »

global chatbot phenomenon

The Global Chatbot Phenomenon

Introduction

We can’t dispute that these bots are on the increase, and we’re not keeping up as quickly as we should. As AI develops further and disruptive technologies become more accessible, any business may now use an AI chatbot to help them compete. The global chatbot market size is expected to reach USD 2,485.7 million by 2028, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 24.9% from 2021 to 2028.

They are being used by businesses across various sectors, such as e-commerce, healthcare, education, travel, etc., to provide instantaneous responses to customers’ inquiries, reduce operational costs, increase sales conversions, and enhance customer satisfaction. For example, Sephora, a leading beauty retailer, uses a chatbot on Facebook Messenger to offer personalized product recommendations, beauty tips, and booking services to its customers. Similarly, Babylon Health, a digital healthcare provider, uses a chatbot on its app to provide medical consultations, prescriptions, and referrals to its users.

These include ensuring the security, privacy, and ethics of chatbot interactions, maintaining the accuracy and relevance of chatbot responses, and overcoming the technical and organizational barriers to chatbot adoption and integration. Therefore, businesses need to adopt a strategic and holistic approach to chatbot development and deployment, taking into account the needs and expectations of their customers, employees, and stakeholders. According to a report by Backlinko, 67% of consumers worldwide used a chatbot for customer support in 2020.

Conversing with them has changed the face of customer service due to its broad adoption. According to Gartner, 38% of companies have plans to introduce a chatbot within the next two years. That’s a forty percent rise in IT adoption.

What is a Chatbot?

Simply said, it is an AI computer that can interact with customers in a way that seems natural by human standards. The purpose of a chatbot is to provide a kind, helpful response to consumers and potential customers anytime they interact with the organization, regardless of the channel they choose to do so. In addition to submitting support requests, communicating with live staff, and sending emails, customers can do all of these things with them.

A primitive example would be a time where you are talking with a telephonic customer service number and had to choose an option to continue, as per your demands. Modern chatbots do the same thing by holding a conversation with customers. This conversation may be in the form of text, voice or a hybrid of both. Based on a recent survey, it was also found that almost 88% of people have at least had one conversation with a chat bot and know what chatbots are.

Chatbots have also become more diverse and specialized over time, thanks to the availability of various platforms and frameworks that enable chatbot development and deployment. Some of the platforms and frameworks that are used to create them include cloud computing services, application programming interfaces (APIs), software development kits (SDKs), chatbot builders, etc. Some of the examples of these platforms and frameworks are Amazon Lex, Google Dialogflow, Microsoft Bot Framework, IBM Watson Assistant, Facebook Messenger Platform, etc.

They have also become more integrated and ubiquitous over time, thanks to the proliferation of various channels and devices that enable chatbot interaction. Some of the channels and devices that are used to interact with chatbots include websites, mobile apps, social media platforms, messaging apps, voice assistants, smart speakers, smart watches, etc. Some of the examples of these channels and devices are WhatsApp, Telegram, Slack, Skype, Alexa, Siri, Google Assistant, etc.

Industry Adoption

Many industries are evolving its customers’ experience by introducing chatbot services in their operations.

In the modern era of customer service environment, messaging a chatbot is intended to give consumers a similar experience to messaging a sales assistant. However, some of these applications are more advanced than others.

We can see that there is a significant rise in the use of chatbots as they are known to lower the load on humans and give better outputs.

The Global Chatbot Phenomenon Read More »

amazon ups its ai game

Amazon Ups Its AI Game

On September 25, 2023, Amazon announced that it would invest up to $4 billion in Anthropic, an artificial intelligence (AI) startup. This is one of the largest investments ever made in an AI company by Amazon, and it signals Amazon’s serious intent to become a leader in the AI field.

What is Anthropic?

Anthropic is a research and development company that is working to develop safe and beneficial artificial general intelligence (AGI). Anthropic’s most popular product is Claude AI competitor for ChatGPT & Bard.

Reasons Amazon Might Have Chosen Anthropic

As of now, amazon has not officially specified the reasons for choosing the anthropic for investment in the AI. Mentioned are the several reasons

  • Through this collaboration, Anthropic will become one of AWS’s largest cloud customers, which might lead to an increase in the number of high-value AI clients using Amazon’s cloud services.
  • Anthropic’s computing requirements align well with those of AWS’s infrastructure.
  • AWS’s AI performance can be enhanced by using Amazon Bedrock to gain access to Anthropic’s base models.

It’s important to note that Amazon’s investment in Anthropic doesn’t restrict the company from forming partnerships with or acquiring other AI businesses in the future.     

Investors are pouring billions of dollars into generative AI startups

Other notable partnerships between tech giants and AI startups include:

  • Google invested in Hugging Face, a startup that provides an open-source platform for building natural language processing applications, as part of its $235 million Series D funding round in August 2023. The round valued Hugging Face at $4.5 billion.
  • Amazon acquired Zoox, a self-driving startup, for about $1.2 billion in June 20203. Zoox had been developing driverless cars with a view to rolling out an on-demand autonomous taxi service since 2014.
  • Nvidia invested in Hugging Face as well as Provino, a startup that develops interconnect protocols for AI applications, in 2023. Nvidia also announced a collaboration with Hugging Face to develop generative AI models using Nvidia’s AI computing platform. The amounts of Nvidia’s investments were not disclosed.
  • Microsoft acquired Nuance, a speech recognition and conversational AI leader, for $56 per share, or about $16 billion, in April 2021. Nuance’s technology was used to enhance Microsoft’s cloud and healthcare offerings.
  • Alphabet’s investment in Parti AI in 2023
  • Intel’s investment in Groq in 2023: $300 million
  • Nvidia’s investment in DeepMind in 2023: Nvidia invested $400 million in DeepMind in 2023

These partnerships highlight the growing interest of tech giants in AI, and their desire to secure access to cutting-edge AI technologies.

Amazon Ups Its AI Game Read More »

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Sustainable blockchain technology has immense benefit for the environment which cannot go unnoticed.

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Featured Reports

Understand the macroeconomic situations that affect the global positioning of countries.

Businesses can better understand how chatbots can advocate their vision.

DeFi helps reduce dependency on traditional methods of transactions.

Creating a sustainable environment for driving multiple countries into a better tomorrow.

Understand how the U.S. discrepancy in accordance to their debt creates a havoc. 

Sustainable blockchain technology has immense benefit for the environment which cannot go unnoticed.