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  • The war for AI talent is heating up

The war for AI talent is heating up

Also: Fake beauty queens charm judges at the Miss AI pageant


In today's newsletter, we delve into the intensifying global competition for AI talent as tech giants and startups alike vie for experts who can spearhead transformative advancements. Hitachi’s ambitious plan to train 50,000 employees in AI underscores the growing corporate focus on leveraging AI across various sectors. Meanwhile, the innovative "Miss AI" pageant breaks new ground by showcasing AI-generated beauty queens, blending digital creativity with social advocacy. Benedict Evans offers insights into the challenges of developing reliable AI products for the mass market, stressing the importance of managing user expectations around AI’s probabilistic nature. On a similar note, researchers are turning to game theory to enhance the accuracy and consistency of AI responses, promising more reliable outcomes. Additionally, we cover Microsoft's pivot on its controversial AI tool, Recall, which will now be disabled by default due to privacy concerns. Lastly, we highlight the Middle East's strategic push to become a significant player in the global AI funding arena, with Saudi Arabia and the UAE leading substantial investment initiatives.


  • 🔥 The war for AI talent is heating up

  • 👨🏻‍💻 Hitachi to train 50,000 employees in AI in push for new businesses

  • 👩‍🦳 Fake beauty queens charm judges at the Miss AI pageant

  • ⚙️ Building AI products - Benedict Evans

  • 🧐 How Game Theory Can Make AI More Reliable

The demand for AI talent is intensifying as tech giants like Microsoft, Google, and Meta scramble to recruit top-tier researchers capable of driving advancements in AI. This surge is largely driven by the rapid evolution of AI technologies and the transformative impact of models like ChatGPT. Companies are offering substantial incentives, often recruiting entire teams without formal interviews, to secure individuals who can innovate and enhance AI systems. Beyond the superstar researchers, there's a rising need for engineers skilled in integrating AI tools into business operations, highlighting a significant shift in required expertise. Consequently, AI talent is now dispersing more widely across various firms and sectors, including burgeoning startups and industries like healthcare, which are seeking to leverage AI for significant advancements. The competitive landscape is further shaped by the movement of talent from big tech firms to nimble startups offering greater autonomy and potential financial rewards.

Hitachi is embarking on an ambitious plan to train 50,000 employees in AI by 2027, aiming to leverage the technology across its diverse sectors, including IT, railroads, and energy. This initiative will cover about 20% of its global workforce, enhancing their capabilities to develop new services and products utilizing generative AI. The training will focus on integrating AI into operational frameworks, data collection, and building advanced language models. This move aligns with Hitachi’s broader strategy to boost its competitiveness by embedding AI across its core businesses. For instance, in the railroad sector, Hitachi is developing AI-driven virtual environments to simulate and manage operational challenges, providing safer and more efficient training for employees. This large-scale AI adoption is part of a growing trend among major corporations to harness AI for expanding business frontiers and improving operational efficiency. Hitachi's partnerships with tech giants like Google, Microsoft, and Nvidia highlight its commitment to staying at the forefront of AI advancements.

The "Miss AI" beauty pageant, held this month, marks a groundbreaking shift in the world of beauty contests by featuring contestants that are entirely AI-generated. This inaugural competition, organized by the U.K.-based online creator platform FanVue, showcases photorealistic images of AI models on social media platforms like Instagram. These AI contestants, created using a blend of off-the-shelf and proprietary AI technologies, have no physical presence but engage audiences through lifelike images and videos. The event has attracted significant attention due to its unconventional nature and the $5,000 prize awarded to the winner. Judges selected 10 finalists from 1,500 entries, with the competition focusing not just on traditional beauty standards but also on the creativity and technological prowess behind these digital models. Each AI finalist, while adhering to conventional beauty norms, also represents various causes, from ocean conservation to LGBTQ advocacy, signaling an effort to combine aesthetics with meaningful messages. Despite the novelty and technological marvel, there is criticism that the AI models still conform to outdated beauty stereotypes, limiting the potential diversity that AI could bring to such contests.

In his essay, Benedict Evans explores the complexities of developing AI products for mass-market applications, particularly when these technologies often provide "wrong" answers. He highlights the inherent uncertainty in generative AI models like ChatGPT, which are designed to offer probable responses rather than precise factual answers. Evans argues that while this probabilistic nature can be a strength in certain contexts, it also poses significant challenges for product design and user interaction. He suggests that successful AI products must either confine their use to specific domains where they can be more accurately controlled or integrate AI seamlessly into functionalities that enhance user experiences without overtly presenting themselves as AI-driven. This approach aligns with how previous technologies have been adopted and integrated, becoming part of everyday tools rather than standalone features. Evans emphasizes the need for AI products to evolve from merely fitting into existing problem frameworks to creating new, innovative experiences that leverage AI's unique capabilities, all while managing user expectations around the technology’s limitations.

Researchers are leveraging game theory to enhance the reliability and consistency of LLMs like ChatGPT, which often produce varying answers depending on how questions are posed. This inconsistency can undermine user trust in these AI systems. A team from MIT has developed the "consensus game" to address this issue, aligning a model’s generative and discriminative capabilities to ensure more accurate and uniform responses. In this game, the AI's two components—the generator, which handles open-ended questions, and the discriminator, which deals with choice-based queries—compete to reach a consensus on the correct answer. This iterative process, played over thousands of rounds, incentivizes the AI to adjust its responses and beliefs to achieve agreement, thus enhancing overall accuracy. Initial experiments showed that LLMs engaged in this consensus game delivered more reliable results, even outperforming much larger models. Beyond improving response consistency, this approach illustrates how game theory can be applied to advance AI’s strategic capabilities, with potential implications for various real-world applications. This innovative method underscores a shift from using AI to master games to employing game-theoretical frameworks to refine AI performance itself.

🛠️ AI tools updates

Microsoft’s recent announcement of its Copilot+ PCs, featuring AI tools like the controversial Recall, has sparked significant privacy and security concerns. Recall, designed to periodically take and store encrypted screenshots of a user’s activity to help them "remember" their interactions, will now be disabled by default following backlash. Users must opt in through Windows Hello and prove their presence to access these screenshots, with added security measures like "just in time" decryption. Critics, including cybersecurity experts, highlighted the potential risks, such as the tool storing sensitive information in a plain-text database, which could be exploited by malware. Microsoft has responded by emphasizing their commitment to evolving user experiences while maintaining privacy and security. Despite these assurances, the feature has drawn scrutiny from regulatory bodies, including the Federal Trade Commission, over concerns of potential anti-competitive practices in the AI sector.

💵 Venture Capital updates

The Middle East, particularly the UAE and Saudi Arabia, is aggressively expanding its footprint in the global AI funding landscape, with ambitions to be recognized as leading tech hubs. Significant investments and partnerships with global tech giants such as Microsoft and Oracle reflect this drive. As of now, the region has attracted billions of dollars and is fostering a burgeoning ecosystem of AI startups, despite being smaller compared to other regions like the US and Europe. Saudi Arabia is notably preparing a $40 billion fund to propel its AI ventures, positioning itself as a major global investor. The UAE, leveraging its early adoption of emerging technologies and government support, has seen robust growth in AI development since 2017, with initiatives like the establishment of AI-focused councils and significant investments in AI startups and research. Israel leads the region in AI VC funds, but the UAE and Saudi Arabia are catching up with targeted investments in high-growth sectors.

🫡 Meme of the day

⭐️ Generative AI image of the day