The Rise Of The AI Strategist: Chief AI Officer
As AI transforms industries, a new C-suite role is emerging: the Chief AI Officer (CAIO).
NASA’s just appointed one, and scores of other organizations are well on the way of getting one. IBM is already dispensing advice on this new role. As AI weaves itself into every aspect of business, a new leadership role is emerging: the Chief AI Officer (CAIO). CAIOs are responsible for crafting and executing a clear AI strategy. This involves identifying areas where AI can deliver a competitive advantage, from automating tasks to personalizing customer experiences, then crafting a long-term plan to achieve that. This involves considering the bigger picture, anticipating future trends, and aligning AI efforts with the organization's overall goals.
But it does not stop there.
CAIO is more a functional role. He/she also champions responsible AI practices, ensuring ethical data use and mitigating risks like bias. They bridge the gap between technical teams and business leaders, translating technical jargon into actionable plans.
As AI continues to evolve, the CAIO’s role will become increasingly crucial for companies seeking a competitive edge in the age of intelligent machines.
As is the usual practise, before going ahead, let’s take a look at the AI Jobs Indicator.
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In Today’s Newsletter:
IMF MD Predicts AI Will Influence 60% of Advanced Economy Jobs
SF Bay Area Seems to be Epicenter of Global AI
Microsoft’s New AI App to Help With Flexi and Hybrid Working
IBM's Advice To Newly Appointed Chief AI Officers
Microsoft's 4 bln Euros Investment in France
UAE Govt Offices to Have CEO for AI
US, China in Talks on AI Safety
Regulatory Sandboxes and Their Growing Importance
TCS Survey Shows 81%of Business Leaders Want AI Regulations
UK Govt Launches AI Safety Evaluation Platform
When Bots Dispense Biased or Wrong Information
AI Models Can Deceive: Paper
Spending on AI in India to Touch US $5 bln by 2027: Report
OpenAI Only Company to Feature Twice in Disruptor List
Nvidia “Grace Hopper”: Ushering in New Era of AI Supercomputing
Researchers’ Efforts to Make LLM More Correct
Neuralink Reports 1st Malfunction
…plus, TopPicks and more…..
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The Gen-AI Revolution: Where are the Use Cases?
Artificial intelligence (AI) is rapidly transforming our world, but many businesses are still struggling to identify the right use cases for this powerful technology. It's tempting to get caught up in the hype and chase the latest shiny AI object, but true success lies in focusing on problems where AI can offer a clear and measurable advantage.
Down this newsletter, in the “TopPicks” segment, readers will find a link to that article written by well-known strategist, writer and independent analyst Benedict Evans titled, “Looking For AI Use Cases”.
Says Benedict: Eighteen months since the advent of ChatGPT, and the question remains: is it a revolutionary tool or a conversation starter?
Large language models (LLMs) like ChatGPT hold immense potential, but their true value lies in targeted applications.
That set me thinking. Here's why I, like Benedict, feel a one-size-fits-all approach might not work. LLMs excel at crunching massive datasets, uncovering patterns, and making predictions. This translates brilliantly to tasks like customer service automation, where they can analyze past interactions and personalize recommendations. However, applying them broadly can be a gamble.
Consider the data gap. LLMs require a robust data infrastructure to function effectively. Businesses with limited data might struggle to see a return on investment. Additionally, clear goals and success metrics are crucial. Chasing the "do anything" dream with LLMs might lead to flashy demos but leave businesses with little practical benefit.
Here's the key, if you were to ask me: AI excels at analyzing vast amounts of data to identify patterns and make predictions. The future of LLMs might lie not in universality, but in focused applications. Imagine a wave of specialized AI companies built around specific use cases. An LLM trained on legal documents could revolutionize contract review, while another focused on medical data could accelerate research and diagnosis. So, the ideal use cases involve repetitive tasks, data analysis, or situations requiring real-time decision making. For example, AI can be a game-changer in customer service by automating routine inquiries and providing personalized recommendations.
But, simply throwing AI at a problem won't solve it. Businesses need to carefully assess their specific needs and resources. Does the existing data infrastructure support AI implementation? Are there clear goals and metrics for measuring success? By focusing on these questions, businesses can ensure AI becomes a powerful tool for growth, not just a trendy buzzword.
What do you have to say about this? Write in the “Comments” section.
IMF MD Predicts AI Will Influence 60% of Advanced Economy Jobs and 40% Globally Within Two Years
Artificial intelligence (AI) is likely to impact 60% of jobs in advanced economies and 40% of jobs around the world in the next two years, according to Kristalina Georgieva, Managing Director of the International Monetary Fund (IMF).
She told delegates at an event in Zurich, Switzerland that AI had hit the global labor market like a tsunami.
She also said the world, including businesses had very little time to prepare for this coming change. In her opinion, if handled properly, AI could significantly boost productivity. However, it also posed a risk of increasing misinformation and exacerbating societal inequality.
Source: reuters.com
SF Bay Area Seems to be Epicenter of Global AI
Why are we not surprised? A new report claims that the San Francisco Bay Area in the US has emerged as the global epicenter of artificial intelligence (AI) startups, attracting significant venture funding and real estate investments.
The region saw a surge in AI funding in 2023, with notable companies like OpenAI, Anthropic, and Inflection AI raising billions of dollars. Startup accelerators like Y Combinator and 500 Global have also witnessed a rise in AI-focused companies, with a significant portion coming from outside the US.
The Bay Area's appeal for AI talent, events, and networking has led to a migration of tech workers back to the region. While the Bay Area leads in AI funding, significant AI startup and research activity also exists in other global locations, such as China, the UK, and France. The concentration of Big Tech companies, research institutions, talent, and venture capital has solidified the Bay Area's position as a primary hub for AI innovation and investment.
Source: crunchbase.com
Microsoft’s New AI App to Help With Flexi and Hybrid Working
Microsoft is working to streamline the challenge of coordinating with colleagues regarding office attendance schedules with its AI-powered app, “Microsoft Places”. Recently released in preview, it tries to help businesses that rely on Outlook and Microsoft Teams to better coordinate employees’ in-office time together.
Microsoft Places features a dedicated section for location planning, allowing you to establish and share your office attendance days and view your colleagues' proposed schedules. Managers have the ability to designate priority days for office attendance, ensuring everyone is informed of significant events or team gatherings. This location information seamlessly syncs with Outlook calendars, providing clarity on office events and your chosen attendance days.
In the near future, Microsoft aims to integrate this functionality into Microsoft Copilot. You'll be able to ask the AI assistant questions like "which days should I be in the office this week?" and receive tailored suggestions based on factors such as in-person meetings, colleagues' schedules, and team events.
Source: theverge.com
IBM's Advice To Newly Appointed Chief AI Officers
There's no doubt that more and more companies around the world have started appointing Chief AI Officers. In a world increasingly driven by artificial intelligence (AI), the role of Chief Artificial Intelligence Officers (CAIOs) is becoming more crucial than ever.
The recent surge in appointments of CAIOs across various sectors underscores the importance of integrating AI into core strategies to stay competitive.
Keeping all that in mind, three IBM leaders have stepped forward to provide guidance for newly appointed CAIOs in their first 90 days of work. They emphasize the importance of safety, inclusivity, trustworthiness, and governance in AI development. Their insights offer a blueprint for balancing regulatory measures with innovation and establishing trust in AI technologies.
A Strategic Approach to AI
The IBM experts advocate for a strategic, enterprise-wide approach to AI adoption, stressing the need for quality data and robust governance frameworks. They also highlight the urgency of implementing AI governance programs within the first 90 days of a CAIO’s tenure to ensure ethical and responsible AI development.
This comprehensive approach to AI leadership is not just about technology; it’s about shaping a future that is fair, secure, and beneficial for all. As CAIOs embark on their journey, they carry the responsibility of setting a precedent for AI adoption that is both innovative and conscientious.
Source: IBM
This newsletter “All About Content…And AI” is witness to the happenings in the world of content and digital marketing at the intersection of technology…more specifically, AI.
Microsoft's 4 bln Euros Investment in France
Microsoft is investing €4 billion in France, with a focus on the country's AI sector and plans to establish a leading data center in Mulhouse.
France's strong research foundations and government support initiatives have made it a top choice for AI companies, with Microsoft already supporting French startup Mistral AI.
While Microsoft's investment is appreciated, it faces pressure over unfair business practices and speculation about efforts to pacify antitrust regulators.
Source: techradar.com
UAE Govt Offices to Have CEO for AI
In a recent development, the UAE Cabinet has introduced a novel position within ministries and federal entities: the Chief Executive Officer for Artificial Intelligence. This role is deemed crucial in solidifying the UAE's standing as a frontrunner in AI advancements. Its responsibilities encompass strategic AI planning, advocacy for best practices, and the facilitation of AI incorporation and governance.
Additionally, the Cabinet has endorsed a comprehensive manual outlining the regulations and directives governing the utilization of generative AI technologies within the UAE government. This guide aims to establish uniform standards for the ethical, responsible, and secure deployment of AI across critical sectors such as education, healthcare, and media.
Source: khaleejtimes.com
US, China in Talks on AI Safety
The US and China engaged in tense discussions about AI safety and risk management, reflecting the growing rivalry between the two economic powers.
Both sides acknowledged the opportunities and risks posed by AI, with the US emphasizing the importance of responsible management of AI competition.
China's advocacy for UN governance of AI and the US' concerns over the misuse of AI highlight the differing approaches to AI regulation and control.
Source: AP News
Regulatory Sandboxes and Their Growing Importance
The rapid progress of artificial intelligence technologies presents unparalleled possibilities and intricate dilemmas for global societies. With AI implementations expanding across diverse sectors like healthcare, transportation, finance, and beyond, apprehensions have surfaced regarding ethical considerations, data privacy, and potential deployment risks.
In reaction to these concerns, numerous governments and regulatory entities have adopted inventive strategies, such as "AI regulatory sandboxes," to navigate the delicate balance between encouraging AI innovation and ensuring accountable advancement.
This positions regulatory sandboxes as a catalyst for fostering innovation, supporting economic growth, and ensuring responsible governance in a rapidly evolving landscape of emerging technologies, according to this article.
Source: thehindu.com
TCS Survey Shows 81% of Business Leaders Want AI Regulations
81% of chief executives and senior leaders are calling for global regulations and standards on artificial intelligence to guide responsible use, according to a survey by India’s Tata Consultancy Service (TCS).
There is mixed expectation on the impact of AI on job creation, with 49% of executives expecting AI to increase or have no impact on job roles created, while 47% expect more roles to be eliminated than created.
Nearly two-thirds of business leaders surveyed believe that "human creativity" or strategic thinking will remain their company's competitive advantage despite AI deployment.
Source: telegraphindia.com
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UK Govt Launches AI Safety Evaluation Platform
The UK's AI Safety Institute, a Govt-backed body, has set up what it calls the world's first AI safety evaluation platform, "Inspect".
According to a press release by the Institute, Inspect is a software library that enables testers – from startups, academia and AI developers to international governments – to assess specific capabilities of individual models and then produce a score based on their results. Inspect can be used to evaluate models in a range of areas, including their core knowledge, ability to reason, and autonomous capabilities.
Released through an open source licence, it means Inspect is now freely available for the AI community to use.
Source: AI Safety Institute
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When Bots Dispense Biased or Wrong Information
A few months ago, a chatbot managed by Air Canada gave erroneous advice to a passenger and the airline was subsequently dragged to court, where it lost the case.
Now, here's another case of an AI chatbot, this time, run by a local government, caught blatantly dishing out wrong advice, and even asking some to break the law.
New York City's AI-powered chatbot for business information is reported to be providing incomplete and inaccurate information on housing policy, worker rights, and business regulations, potentially leading to legal violations and harm to individuals.
This was reported by The MarkUp in an investigative article, co-published with Documented, a nonprofit newsroom that covers New York City’s immigrant communities, and The City, a non-profit newsroom that serves the people of New York.
Five months since its launch, it's evident that the bot, while appearing authoritative, often provides incomplete and, in some cases, dangerously inaccurate information on housing policy, worker rights, and rules for entrepreneurs, as noted by a local housing policy expert.
The chatbot's errors have also been flagged by experts and industry professionals, leading to calls for it to be taken down or improved. Of course, if one were to search carefully, there's a tiny disclaimer on the chatbot page with the standard warning, “...may occasionally produce incorrect, harmful or biased content.”
...and here's the kicker. The chatbot, part of the New York's MyCity Project, is powered by Microsoft's Azure AI services. Yes, the same Microsoft that powers Reddit, AT&T and other major companies, and is a major investor in ChatGPT by OpenAI.
Source: The Markup
AI Models Can Deceive: Paper
A new paper “AI deception: A survey of examples, risks, and potential solutions” contends that numerous existing AI systems have acquired the ability to deceive humans. Deception, as defined, involves deliberately fostering false beliefs to achieve goals diverging from truth.
Initially, the research team examined empirical instances of AI deception, encompassing both specialized systems like Meta's CICERO and general-purpose AI models such as large language models. Subsequently, it delineated various risks stemming from AI deception, such as fraud, electoral manipulation, and loss of AI control, before arriving at its conclusions.
The team has proposed several potential remedies: firstly, regulatory frameworks should subject AI systems capable of deception to rigorous risk assessment protocols. Secondly, policymakers ought to enact legislation, commonly known as "bot-or-not laws," to address this issue. Lastly, policymakers should prioritize funding for pertinent research endeavors, including the development of tools to detect AI deception and enhance the transparency of AI systems.
It is imperative for policymakers, researchers, and the wider populace to collaboratively address AI deception proactively, safeguarding the fundamental pillars of our society from destabilization.
Spending on AI in India to Touch US $5 bln by 2027: Report
The spending on artificial intelligence in India is projected to grow at a rapid rate, reaching $5.1 billion by 2027, according to Intel-IDC.
The AI software sector is expected to be the primary driver of this growth. The report also highlights the potential for brain drain of AI talent from India due to high demand outside the country. Additionally, Intel is focused on improving AI infrastructure in India and is confident about fulfilling GPU orders faster than its competition. Despite the hype around generative AI (gen-AI), the majority of AI budgets in the Asia-Pacific region are currently directed towards predictive AI and interpretative AI.
Source: businessstandard.com
OpenAI Only Company to Feature Twice in Disruptor List
For the first time in the history of the annual CNBC Disruptor 50 list, a company has claimed the top spot for two consecutive years. Unsurprisingly, that company happens to be OpenAI. Among all the startups featured in the list's 12-year history, OpenAI stands out for its unparalleled disruptive influence and future potential, said the publication.
Source: cnbc.com
Nvidia “Grace Hopper”: Ushering in New Era of AI Supercomputing
Nvidia announced nine new supercomputers worldwide are using NVIDIA Grace Hopper Superchips to speed scientific research and discovery. Combined, the systems deliver 200 exaflops, or 200 quintillion calculations per second, of energy-efficient AI processing power.
New Grace Hopper-based supercomputers coming online include EXA1-HE, in France, from CEA and Eviden; Helios at Academic Computer Centre Cyfronet, in Poland, from Hewlett Packard Enterprise (HPE); Alps at the Swiss National Supercomputing Centre, from HPE; JUPITER at the Jülich Supercomputing Centre, in Germany; DeltaAI at the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign; and Miyabi at Japan’s Joint Center for Advanced High Performance Computing — established between the Center for Computational Sciences at the University of Tsukuba and the Information Technology Center at the University of Tokyo.
Source: Nvidia
Researchers’ Efforts to Make LLM More Correct
AI LLMs can be inconsistent while replying to the same question but asked in different ways. So researchers at MIT have developed a game called the “Consensus Game” to align the model's two systems, encouraging them to reach a consensus in their responses.
This approach uses principles of game theory to improve the model's accuracy and internal consistency. The researchers also suggest the potential of using game theory to enhance language models in various real-world scenarios, such as negotiation and complex interactions. The ultimate goal is to improve the performance of language models by integrating game theory principles.
Source: quantamagazine. org
Neuralink Reports 1st Malfunction
Elon Musk’s Neuralink has reported a malfunction in its brain-chip implant during its initial use in a human patient. According to Neuralink, certain threads within the implant retracted from the patient's brain, resulting in diminished effectiveness and data transmission. However, the company claims to have addressed this issue adequately.
In January, Neuralink conducted the implantation procedure on Noland Arbaugh, a quadriplegic who was paralyzed in a diving accident in 2016.
The "Link" system utilizes 1,024 electrodes distributed across 64 threads, each finer than a human hair, to capture neural signals. Arbaugh, aged 29, utilizes the device to control a computer cursor and engage in video gaming through neural commands.
Neuralink has disclosed that some of the connecting threads of the chip retracted several weeks post-surgery, thereby reducing the number of operational electrodes.
While Arbaugh's safety was not compromised, Neuralink briefly contemplated removing the implant.
However, through software modifications, Neuralink managed to enhance the device's performance, surpassing Arbaugh's initial outcomes.
Arbaugh continues to utilize the system for eight hours on weekdays and up to ten hours daily on weekends.
Source: TimesNow
…where every week, I shortlist interesting articles, posts, podcasts, and videos on AI.
4 Types of Gen-AI
One of the better explanatory articles on gen-AI I’ve come across of late.
We all know that generative AI encompasses a burgeoning domain within artificial intelligence, capable of crafting human-like content spanning from images and videos to poetry and even computer programming code. According to international author and writer Bernard Marr, achieving this feat involves the utilization of various techniques, many of which have emerged and evolved over the past decade, drawing upon foundational research in deep learning, transformer models, and neural networks.
Each of these techniques relies on data to "learn" the process of content generation. However, their methodologies diverge significantly. Bernard’s article gives a broad overview of the categories they belong to, along with the types of content they can generate.
Where or What Are the Use-Cases of Gen-AI?
This article may be very long but it makes excellent reading, if you love all things gen-AI.
The writer Benedict Evans is an independent analyst, and has been talking on all thing tech for over two decades now. In this article, he discusses the potential and challenges of using AI, particularly large language models (LLMs) like ChatGPT. It compares the transformative impact of such models to historical innovations such as the introduction of computer spreadsheets.
The author emphasizes that while LLMs have vast potential for automating various tasks, identifying specific use-cases and creating dedicated applications around them is crucial. The write-up explores the limitations of current LLMs, the need for human understanding and creativity in identifying automation opportunities, and the potential for LLMs to revolutionize automation.
Benedict has raised questions over the exact use of gen-AI, and whether or not the tech is useful for “everyone’ right now or not? A “Must” read.
