Tag: artificial intelligence

From Sci-Fi to Reality: Unraveling the Risks of Superintelligence | Blog

Superintelligence promises incredible advancements and solutions to the world’s biggest challenges, yet it also presents an ominous threat to society. As the lines between innovation and catastrophe blur, understanding the risks of AI is crucial. Read on for recommendations for moving forward in this uncharted territory.

Generative Artificial Intelligence’s emergence has led enterprises, tech vendors, and entrepreneurs to explore many different use cases for this disruptive technology while regulators seek to comprehend its wide-ranging implications and ensure its responsible use. Learn how enterprises can leverage GAI in our webinar, Welcoming the AI Summer: How Generative AI is Transforming Experiences.

Concerns persist as tech visionaries warn that AI might surpass human intelligence by the end of the decade. Humans are still far from fully grasping its potential ramifications and understanding how to collaborate with the technology and effectively mitigate its risks.

In a groundbreaking announcement in July, OpenAI unveiled that it has tasked a dedicated team with creating technologies and frameworks to control AI that surpasses human intelligence. It also committed to dedicating 20% of its computing resources to address this critical issue.

While initially exciting, the prospect of superintelligence also brings numerous challenges and risks. As we venture into this uncharted territory, understanding AI’s evolution and its potential implications on society becomes essential. Let’s explore this further.

Types of AI

AI can be broadly categorized into the following three types:

  • Narrow AI

Narrow AI systems are designed to excel at specific tasks, such as language translation, playing chess, or driving autonomous vehicles. Operating within well-defined boundaries, they cannot transfer knowledge or skills to other domains. Common examples include virtual assistants like Siri and Alexa, recommendation algorithms on streaming platforms, and image recognition software.

  • General AI

General AI possesses human-like cognitive abilities and can perform various intellectual tasks across various domains. Unlike narrow AI, general AI has the potential to learn from experiences and apply knowledge to different scenarios.

  • Super AI (Superintelligence):

Super AI represents a hypothetical AI that surpasses human cognitive abilities in all domains. It holds the promise to solve complex global challenges, such as climate change and disease eradication.

Tech thinkers across the globe have raised an alarm

Amidst growing concerns about the risks of superintelligence, the departure of Geoffrey Hinton, known as “the Godfather of AI,” from Google was one of the most significant developments in the AI realm. Hinton is not alone in his concern about AI risks. More than 1,000 tech leaders and researchers have signed an open letter urging a pause in AI development to give the world a chance to adapt and understand the current developments.

These leaders emphasized that development should not be done until we are certain that the outcomes will be beneficial and when the AI risks are fully known and can be managed.

In the letter, they highlighted the following five key AI risks:

  1. Machines surpassing human intelligence: The prospect of machines becoming more intelligent than humans raises ethical questions and fears of losing control over these systems. Ensuring that superintelligence remains beneficial and aligned with human values becomes crucial
  2. Risks of “bad actors” exploiting AI chatbots: As AI technologies evolve, malicious actors can potentially exploit AI chatbots to disseminate misinformation, conduct social engineering attacks, or perpetrate scams
  3. Few-shot learning capabilities: Superintelligent AI might possess the ability to learn and adapt rapidly, presenting challenges for security and containment. Ensuring safe and controlled learning environments becomes essential
  4. Existential risk posed by AI systems: A significant concern is that superintelligent AI could have unintended consequences or make decisions that could jeopardize humanity’s existence
  5. Impact on job markets: AI’s rapid advancement, especially superintelligence, might disrupt job markets and lead to widespread unemployment in certain sectors, necessitating measures to address this societal shift

As we already have seen some risks associated with this technology materialize, cautiously approaching the advancement of its progress is necessary.

Recommendation for moving forward

To mitigate AI risks and the risk of superintelligence while promoting its development for positive societal outcomes, we recommend enterprises take the following actions:

  • Create dedicated teams to monitor the development – The government needs to appoint relevant stakeholders in regulatory positions to monitor and control these developments, particularly to protect the large population that does not understand the technology from its potential consequences
  • Limit the current development – As the letter suggested, the government should implement an immediate moratorium on developing and using certain types of AI. This pause would give everyone enough time to understand the technology and associated risks better. While Italy has used its legal architecture to temporarily ban ChatGPT, efforts like this will not have a significant impact if carried out individually
  • Define policies – Regulatory agencies should start working on developing policies that direct researchers on how to develop the technology and define key levels for alerting regulatory agencies and others
  • Promote public awareness and engagement – Promoting awareness about AI and superintelligence is crucial to facilitate informed debates and ensure the technology aligns with societal values
  • Form international collaborations – Isolated initiatives won’t help the world. Larger collaboration among governments to define regulations and share knowledge is needed

While new technologies have always brought changes to the existing norms, disrupted established industries, and transformed societal dynamics, ensuring these advancements are beneficial to a larger audience is essential.

To discuss the risks of Generative AI, its use cases, and its implications across different industries, contact Niraj Agarwal, Priya Bhalla, and Vishal Gupta.

Intelligence Just Got Real: IT Companies Hard-pivot to Generative AI | In the News

Technology services provider Infosys has announced it is entering into a framework agreement with one of its existing strategic clients to provide artificial intelligence (AI) and automation-led development.

Peter Bendor-Samuel, Chief Executive Officer (CEO) and Founder of Everest Group, shared that all technology services companies – particularly India-based ones – are aggressive about riding the AI wave. “We see a lot of AI washing, provider firms claiming they are doing a lot. However, we believe we are at the start of the wave and most enterprise firms (customers) are still getting organized. We think much of the dialogue from the service provider community is early positioning and posturing,” he adds.

Read more in Business Standard.

The Possibilities for Generative AI in Sourcing | LinkedIn Live


The Possibilities for Generative AI in Sourcing

View the event on LinkedIn, which was delivered live on Tuesday, June 20, 2023.

The rise of generative AI (GAI), particularly ChatGPT, has captured significant attention, and many companies are actively exploring ways to leverage the transformative technology. 💡

Watch for a free-flowing discussion as we explore the potential benefits, challenges, and considerations of incorporating GAI into the sourcing landscape. 🌟🔎

We discuss current and future use cases, best practices, and strategies for effectively leveraging GAI to improve processes such as supplier identification, market research, contract analysis, risk assessment, and more. Sourcing professionals should attend this session to learn how to utilize this fast-evolving technology – and what to watch out for. 💡

What questions did the event answer for the participants?

  • As a sourcing professional, where are the opportunities to integrate GAI into your processes? 💻
  • What concerns do you need to watch out for? ⚠️
  • Which technology platforms and providers are leading the way? 🚀

Meet The Presenters

Fong Amy Refresh gray square
Everest Group
Vignesh K Refresh gray square
Vice President
Everest Group
Founder and Chief Strategy Officer​

Generative AI – Redefining the Experience Design and Development Process | Blog

Generative Artificial Intelligence (GAI) holds the potential to revolutionize the experience design and development process by creating unique personalized marketing content. Read on to learn about the opportunities, challenges, and implications of GAI for enterprises and service providers.

You can also hear about the use cases, the limitations and risks, and the industry’s predicted response in our webinar, Welcoming the AI summer: How Generative AI is Transforming Experiences.

From rule-based systems merely capable of automating set functions to deep learning algorithms that can accurately comprehend natural human language nuances, Artificial Intelligence (AI) undoubtedly has come a long way.

Today, AI is at a juncture where its capabilities are no longer restricted to automating repetitive tasks. Generative AI – the latest version of this technology – has taken the industry by storm this year by entering the arena of human creativity.

While GAI is flooding the market with a plethora of unique use cases, it particularly has the potential to disrupt the experience design and development process by optimizing the content supply chain and streamlining the UX/UI design process. Let’s explore this further.

What is Generative AI?

Everest Group defines Generative AI as a variant of AI technology based on deep learning Generative Adversarial Networks (GANs) and Transformer models, having the ability to provide convincingly unique content in the form of text, imagery, video, audio, and synthetic data.

Although the technology has been around for the last five decades, it has recently gained momentum due to advancements in hardware computation power, maturity of AI models, and availability of high-quality contextualized training data sets.

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Exhibit 1: Definition and evolution of GAI technologyPropelled by investments from giants such as Microsoft, Google, and Amazon, the market is witnessing a huge influx of start-ups focused on consistently identifying and operationalizing new Generative AI use cases.

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Exhibit 2: Start-ups pioneering unique use cases in the GAI space

How can GAI help marketers?

As personalization becomes the centerpiece of every marketing strategy, the never-ending demand for real-time contextualized content puts a lot of pressure on creative teams. This is where GAI comes in. Be it content creation or user interface/user experience (UI/UX) design, the technology can create a scalable creative engine for personalized marketing.

The industry is acting fast to streamline the marketing creative process by adopting GAI. Experience leader Adobe has launched the Firefly family of proprietary GAI models that enable image, audio, video, and 3D model creation through mere text prompts. On the other hand, AI leader NVIDIA has introduced the GauGAN tool that can generate realistic images from sketch drawings by artists.

GAI – The brainstorming partner for idea generation across industries

While content remains key, enterprises also are investing in GAI models in vertical markets to power industry-specific use cases to brainstorm and generate creative ideas.

 The following industries are rampantly adopting GAI technology:

  • Manufacturing: General Motors partnered with Autodesk to use GAI to design a new seatbelt bracket that was 40% lighter and 20% stronger than the original design
  • Healthcare: GAI also is being applied in drug design with companies such as Insilico Medicine using its Chemistry42 GAI platform to generate novel chemical compounds for new medicines
  • Architecture: Architecture firm Skidmore, Owings & Merrill (SOM) has created a GAI tool called SOM Computational Design for generating design options for buildings
  • Retail: Levi Strauss has partnered with Lalaland.ai to design hyper-realistic AI-generated model avatars for promoting diversity in terms of body type, age, and skin color

While AI has leaped in maturity from automating unproductive repetitive tasks to generating unique content via human-led prompts, it still lacks the finesse of a human touch. Therefore, the technology can act as a co-pilot for the creatives, but it’s not yet at a stage where it can provide customer-ready outputs through prompts. Instead of instilling fears about the technology replacing humans, enterprises must embrace the magnitude of the impact it can have on workforce productivity.

Mitigating GAI technology risks

The technology is a game changer, but it comes with substantial challenges related to output accountability, model bias, privacy compliance, talent shortage, system integration, and the cost associated with deploying large AI models.

 While Italy has banned ChatGPT and other European nations have expressed concerns about the technology, pioneers such as Adobe and Salesforce are relentlessly trying to mitigate these risks by developing plagiarism checkers, establishing compensation structures for creative professionals, upskilling talent, and adopting fair representation learning models to counter model biases.

Implications for service providers

With announcements of Accenture’s GAI Center of Excellence, Deloitte Digital’s dedicated GAI practice, Infosys embedding GAI into software development tools, and TCS developing an in-house enterprise-grade solutioning platform using GAI, service providers need to take a cue and move fast to cement a strong understanding of Generative AI functioning and the ecosystem.

Providers also have to bring top leadership up to speed on the Generative AI landscape, flesh out a detailed narrative discovering enterprise priorities, embed GAI in solution and service delivery for efficiencies and productivity, and harness GAI technology’s true potential by integrating it with business applications.

For more insights on Generative AI, contact Vaani Sharma.

HIMSS23 Highlights: Focus on Integration, Generative AI, and Increased Emphasis on Risk Mitigation | Blog

Artificial Intelligence (AI), technology integration, and consumerization are among the key trends driving the future of healthcare, a glimpse into the horizon at HIMSS23 showed. Read on to learn takeaways from Everest Group analysts who attended the recent global healthcare conference.

More than 35,000 healthcare leaders converged in Chicago last week to share ideas, highlight investments, showcase demos, and shape the future at HIMSS23. Technology integration, value realization, and risk avoidance dominated conversations at this year’s more strategic and connected conference focused on finding solutions to urgent issues.

Here are the three main themes we saw at HIMSS23:

  • Integration is the key to realizing value

Integration was a major topic, as many organizations struggle to stitch together various composable platforms. While microservices have enabled precision and faster outcomes for specific use cases, these independent solutions often do not communicate with each other, which can hinder value realization. Many stakeholders we interacted with highlighted the desire to explore ways to better integrate these platforms.

  • Generative AI is attracting attention

Generative AI, like ChatGPT, and its potential applications is creating a lot of excitement. Major technology companies such as Microsoft and Google are leading the way in developing innovative uses for AI in healthcare, including creating new health applications. While some early examples of AI in healthcare show promise, such as voice dictation that help doctors document patient information more efficiently, how AI will address broader healthcare challenges such as staffing shortages, physician burnout, and rising costs remain to be seen.

  • Consumerization of healthcare will continue to grow

Putting the patient at the center of healthcare was another recurring theme, with a focus on designing healthcare systems and technologies that are intuitive and seamless for users. The increased emphasis on user experience has been influenced by the consumer world, where these types of technologies are the norm. The coming years are likely to bring a greater focus on patient portals, wearable health solutions, and virtual care delivery technologies to improve patient/member experience.

How was HIMSS different this year?

WhatsApp Image 2023 04 20 at 4.04.44 PM

The annual HIMSS conference returned to Chicago, with attendees noting a greater sense of urgency and action in meetings versus prior events in Orlando and Las Vegas. A large number of healthcare information and technology companies attending were focused on emerging enterprise priorities around value-based care (VBC) and interoperability.

Leaders engaged in meatier discussions focused on integration, value realization, and risk avoidance. The conversations showed that healthcare enterprises are looking for solutions to get more out of their technology, budgets, and resources in today’s challenging environment.

The large post-pandemic turnout demonstrated the appetite for in-person interaction. Event organizers focused on creating more focused opportunities for attendees to gather and have relaxed and candid conversations with friends, colleagues, and clients, which have been difficult to replicate virtually.

Overall, interacting with industry leaders influencing the next stage in healthcare technology at HIMSS23 was an illuminating experience for Everest Group analysts Abhishek Singh and Manu Aggarwal, who are available to share their insights.

Continue reading about the healthcare industry and the trends influencing decision-making by healthcare payers in our blog, The Recessionary Conundrum: What Lies Ahead for Healthcare Payers?

Generative AI and ChatGPT: Separating Fact from Fiction | LinkedIn Live


Generative AI and ChatGPT: Separating Fact from Fiction

View the event on LinkedIn, which was delivered live on Thursday, April 13, 2023.

If you haven’t experimented with ChatGPT yet, you have at least been following the recent buzz⚡.

💻ChatGPT is one recent example of Generative AI that companies are jumping into. However, while the technology itself has immense potential, much of the recent adoption 👥 has been driven by hype .

What exactly is Generative AI? It is an evolved form of Artificial Intelligence (AI) technology that generates new content in the form of text, images, videos, audio, codes, and more – consensus is that it will influence enterprises and providers significantly.

📢 In this LinkedIn Live, we will provide buyers and providers insights into the latest developments and opportunities, as well as the challenges and possible misconceptions in this dynamic market. The speakers will also discuss how organizations can benefit from Generative AI and what factors to consider while using and investing in it.

What questions does the event address?

✅ What are the strengths and limitations of Generative AI (and ChatGPT) in its current form?
✅ What are some high-value applications and use cases?
✅ What do enterprises and service providers need to keep in mind while adopting Generative AI?
✅ What are the major challenges and best practices to assist adoption?

Meet The Presenters

Andrew Burgess Headshot square
AI Strategist and Ethicist
Founder & CEO, Greenhouse Intelligence
Rickard David
Everest Group
Vijayan Anil
Everest Group

ChatGPT – A New Dawn in the Application Development Process? | Blog

ChatGPT, the advanced Artificial Intelligence (AI) chatbot that’s taken the world by storm, can potentially accelerate various stages in the Software Development Lifecycle (SDLC), from gathering requirements to design and testing, and also enhance developers’ productivity, among other benefits. But it still has limitations. Read on to learn more.   

ChatGPT made headlines when it reached 1 million users in just five days after being unveiled in November 2022. Not only was the tech community awed, but it also has interested a wider audience, from students to industry veterans, and attracted more than 100 million users by the end of January 2023.

ChatGPT and other AI chatbots, such as DALL-E, are poised to radically disrupt multiple professions, including education and healthcare. In our ongoing coverage of this trending topic, we’ll explore how these recent developments may rapidly advance the application development process.

What is ChatGPT, and why is it creating major upheaval?

ChatGPT (Chat Generative Pre-Trained Transformer) is a chatbot built by AI firm OpenAI. It is based on Generative Pre-Trained Transformer (GPT-3) architecture, a neural network Machine Learning (ML) model that generates human-like responses to natural language text inputs. Its ability to converse like a human, answer follow-up queries, and reject inappropriate queries makes it more special than its predecessors. Its capabilities include language translation, text summarization, and text generation.

We tried our hands on ChatGPT and asked it to write a blog on itself, and the results amazed us. See the exhibit below for the blog that ChatGPT generated.

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Next, let’s explore in more detail how ChatGPT could be embedded in the Software Development Lifecycle (SDLC) to create applications and the associated benefits.

The avant-garde movement in application development

While low-code/no-code and AI-assisted application development made leaps and bounds in this field, ChatGPT has the potential to step up the game even further. This potent AI tool can be used to accelerate different processes at various phases of the SDLC, leading to faster development cycles, enhanced productivity of developers, and quicker value delivery to enterprises.

Here are the potential benefits of each phase:

Requirements gathering: ChatGPT can significantly simplify the requirements gathering phase by building quick prototypes of complex applications. It also can minimize the risks of miscommunication in the process since the analyst and customer can align on the prototype before proceeding to the build phase

Design: DALL-E, another deep learning model developed by OpenAI to generate digital images from natural language descriptions, can contribute to the design of applications. In addition to providing user interface (UI) templates for common use cases, it also may eventually be deployed to ensure that the design of a given application meets regulatory criteria such as accessibility

Build: ChatGPT has the capability to generate code in different languages. It could be used to supplement developers by writing small components of code, thus enhancing the productivity of developers and software quality. It even can enable citizen developers to write code without the knowledge of programming language

Test: ChatGPT has a major role in the testing phase. It can be used to generate various test cases and to test the application just by giving prompts in natural language. It can be leveraged to fix any vulnerabilities that could be identified through processes such as Dynamic Code Analysis (DCA) and perform chaos testing to simulate worst-case scenarios to test the integrity of the application in a faster and cost-effective way.

Maintenance: ChatGPT can significantly improve First Contact Resolution (FCR) by helping clients with basic queries. In the process, it ensures that issue resolution times are significantly reduced while also freeing up service personnel to focus their attention selectively on more complex cases.

While ChatGPT has an important role to play in automating more cognitive tasks in the SDLC, users must be aware that security and privacy concerns with the current version still need to be properly addressed.

Now let’s cover a few issues with the tool.

 Five possible roadblocks to ChatGPT adoption

  • Privacy and security – Privacy and security are concerns with the current tool. As it learns from each query, keying in any sensitive data would have drastic repercussions on enterprises. Amazon has reportedly warned employees to not put confidential data on ChatGPT, fearing security concerns
  • Limited knowledge – ChatGPT currently is not connected to the internet and has limited knowledge of the world and events after 2021, meaning the code it generates will not be in line with the latest security patches
  • Potential Bias – While OpenAI has added guardrails against bias in responses, users can occasionally get around this by rephrasing their questions or asking the program to ignore its guardrails
  • Inaccurate responses – ChatGPT responds to queries based on the patterns it learned from the training dataset and also can generate fictitious responses that cannot be verified for accuracy. Although the tool is still evolving, inaccuracy in responses can be a major hindrance to its adoption
  • Energy Consumption – As an advanced AI-based tool, ChatGPT takes a huge amount of computing power to process the information, leading to high energy consumption and carbon emissions. With environmental, social, and governance (ESG) becoming a key mandate across geographies, enterprises may be apprehensive about large-scale adoption

The way forward

ChatGPT is seeing rampant adoption among the developer community, and as it gains further traction, enterprises need to ensure suitable governance models are in place. Service providers need to collaborate with tech players like OpenAI and DeepMind to proactively shape the market and build capabilities for efficient application development.

As details unfold on how this technology will revolutionize the application development process, enterprises and service providers need to closely monitor this space and make proactive investments – clearly, the cost of missing out is too great.

For our other recent blogs on how ChatGPT will impact various industry sectors, see Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term and ChatGPT Trends – A Bot’s Perspective on How the Promising Technology will Impact BPS.

We’ll investigate the implications of ChatGPT for the technology services industry in more detail in a follow-up blog.

To discuss how ChatGPT will impact the application development process, please reach out to [email protected], [email protected], or [email protected].

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