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What’s happening in AI right now

A look at talent trends

A wave of AI integration is sweeping through a board swath industries, reshaping organizational structures, workforce strategies, and core operations. Recent developments at TransRe, S&P Global, Dell, and BMW illuminate the varied approaches companies are taking to harness AI's potential.

AI Ascends the Corporate Ladder

TransRe, a major reinsurance player, has made a bold move by appointing Otakar Hubschmann as Chief Artificial Intelligence Officer and forming a dedicated Artificial Intelligence Team (TRAIT). This strategic decision elevates AI to the C-suite, signaling its critical importance to the company's future. By having TRAIT report directly to the COO, TransRe ensures AI initiatives receive top-level attention and support.

This creation of a C-level AI position could set a precedent, potentially sparking a trend across industries. As companies grapple with AI's growing impact, we may see a proliferation of AI-focused executive roles, fundamentally altering the composition of leadership teams.

AI Literacy a New Corporate Imperative

While TransRe focuses on specialist AI teams, S&P Global is taking a more comprehensive approach. The financial services giant is partnering with Accenture to train its entire 35,000-employee workforce in generative AI skills. This mass upskilling initiative aims to boost productivity across the organization and position S&P Global at the forefront of AI adoption.

S&P Global's strategy raises intriguing questions about the future of work in AI-enabled organizations. How will widespread AI skills impact job roles and organizational structures? What challenges might arise in maintaining curriculum relevance in a rapidly evolving AI landscape? The success or failure of their ambitious effort could serve as a blueprint for other large enterprises considering similar scaled training initiatives.

The Double-Edged Sword of AI Efficiency

While S&P Global invests in AI training, Dell is perhaps leveraging AI as a catalyst for significant organizational changes. The tech giant's recent decision to cut 12,500 jobs as part of an AI-driven restructuring highlights the potential disruptive impact of AI on traditional workforce models.

Dell's move presents a stark contrast to S&P Global's approach, illustrating the complex decisions companies face in the AI era. How can organizations balance AI-driven efficiency gains with the need to retain valuable human expertise? What strategies can minimize the negative impacts of AI-related job displacements?

AI Meets the Assembly Line

This AI revolution isn't limited to white-collar work. BMW's recent trial of the Figure 02 humanoid robot at its Spartanburg factory demonstrates AI's potential to transform physical processes as well. This experiment in using AI-powered robots for complex assembly tasks represents a significant step towards the factory of the future.

BMW's cautious approach, partnering with external AI specialists rather than developing in-house solutions, offers an interesting contrast to companies like Tesla that are heavily investing in their own robotics and AI capabilities. This strategic difference echoes the varied approaches we see in other sectors, from TransRe's specialist team to S&P Global's company-wide upskilling.

News roundup

The top stories in AI today.

TALENT TRENDS

The people moves you need to know

• OpenAI's AI dominance threatened by executive departures

• TransRe appoints Chief AI Officer and restructures data science team

• S&P Global partners with Accenture to train 35,000 employees on AI

• Dell cuts 12,500 jobs in major restructuring effort focused on AI-driven growth

• Why You Need a ‘Second Brain’ and the AI Tools to Build One

NEW LAUNCHES

The latest features & products in AI innovation.

• EdgeCortix develops energy-efficient AI chips and software for edge computing, delivering near cloud-level performance

• AI-powered real-time translation revolutionizes 911 services for non-English speakers

• New AI technique revolutionizes document processing with text-image augmentation.

• Lamborghini embraces electrification while preserving its iconic brand essence

GADGETS

Computers, phones, wearables & other AI gizmos.

• Gemini AI expands to personal Gmail accounts on Android, offering AI-powered email

• Apple may launch AI features on Macs in EU despite iOS restrictions

• Google unveils AI-powered Nest Thermostat and Google TV Streamer, expanding smart home lineup

• Samsung to bring Galaxy AI features to mid-range Galaxy A series phones

• Realme's AI-powered Watch S2 brings premium features to budget smartwatches

VC

The key trends and rounds

• Quantum startup Riverlane raises $75M to advance error correction technology

• AI infrastructure boom spawns billion-dollar cloud startups catering to specialized computing needs

• AI startups dominate Forbes Cloud 100 Rising Stars list

• Canadian startup Perceptive Space raises $2.8M to develop AI-powered space weather prediction platform

ROBOTICS

From Humanoids to software

• Tesla pivots from automaker to AI and robotics company?

• Turkish high school student creates AI robot guide dog for the visually impaired

• BMW trials AI humanoid robot for car assembly tasks at US factory

• Oxford Dynamics’ Life-Saving Robot Is Purpose-Built for Hazardous Environments

• Robot Dentist Performs World’s First Autonomous Dental Procedure

FINANCE & ECONOMICS

Economics + the movers & shakers on Wall Street.

• AI Investment Bubble Shows Signs of Potential Burst Amid Growing Skepticism

• AI revolutionizes financial services through data-driven insights and operational enhancements.

AI research changing the world

The latest breakthroughs and most pivotal papers — broken down in language anyone can understand.

Google Research Unveils Chain-of-Thought Prompting

Imagine an AI that doesn't just respond with quick, isolated answers, but one that reasons through problems step by step, much like a human would. This is the vision brought closer to reality by Google Research's latest findings. The team has developed a method called "chain-of-thought prompting," which significantly enhances the reasoning capabilities of large language models. This breakthrough is not just a technical marvel; it has substantial implications for how we might interact with AI in the future, potentially transforming various sectors, including education, healthcare, and business.

The research demonstrates that when large language models, such as PaLM 540B, are given a sequence of reasoning steps (a chain of thought), their performance on complex tasks improves dramatically. For instance, using just eight chain-of-thought exemplars, PaLM 540B achieved state-of-the-art accuracy on the GSM8K math word problems benchmark, outperforming models that had been fine-tuned on the task. This is particularly noteworthy since the approach doesn't require extensive datasets for training, meaning a single model can tackle a variety of tasks while retaining its versatility.

However, the magic truly happens at scale. Their research indicates that the benefits of chain-of-thought prompting become apparent with models around the 100B parameter mark, which aligns with the current frontier of model sizes. Smaller models don't seem to reap the same benefits, often producing fluent but illogical reasoning paths. This suggests that the ability to perform abstract symbol manipulation and multi-step reasoning is an emergent property of large language models.

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