30 years in journalism has sharpened my mind.

I've spent years in AI.

And months researching China and the US as they fight silently for AI supremacy.

$500bn in The Stargate Project does not come close to the value China has created integrating AI into every aspect of its society and economy. But the truth is, they won before the US even woke up to AI's potential. China's superapps - forget homescreens, because you only need one icon to run your life in the Republic - were simply laying the foundation for where we are, today.

But let's have a debate, nonetheless.

East v West: which is best?

I've been working on a business intelligence platform leveraging AI and 30 years in journalism and content strategy. It's the toughest professional project of my career. And I have no idea if I will win. But just like life, Zeitgeist is all about the journey, not the destination. What I am learning is more important than any long form feature we might generate. Knowledge graphs, ontologies, taxonomies, and patience. Hope you will stick around on this crazy adventure.

I'm Dave Thackeray - leadership coach, content strategist, and endlessly curious Berlin-based berk.

Email me at dave@wordandmouth.com to test Zeitgeist for your business.

Recruitment is being radically remodelled by AI.

And according to a brand new piece of research, AI is already humiliating humans at hiring.

Hear the story behind the headlines that AI-led interviews increase job offers by 12%, job starts by 18%, 30-day retention by 17% - and when offered the choice, 78% of applicants choose the AI recruiter.

Read the research

Google DeepMind's Demis Hassabis and his team have a bold mission: penetrating the 4D chess game that's AI embracing our ever-changing biological, physical world.

Taking a snapshot is one thing. Remembering the molecular topology and their constant changes of state is truly what separates fact from fiction.

It seemed like an impossible target to hit. Until M3-Agent, the work of researchers associated with ByteDance at Shanghai Jiao Tong University, showed up with long-term multimodal memory - allowing the agent to see, hear, remember, and reason just like humans.

M3-Agent's potential is groundbreaking.

Here are just three use cases that will blow all our minds:

• Autonomous robotics: Robots in homes or warehouses remember object locations, user habits, and past errors, adapting tasks dynamically, such as a caregiver bot recalling a patient's routines for personalized aid
• Enhanced surveillance: Security systems analyse live video/audio feeds, building memory of normal patterns to detect anomalies, predict threats, and reason through scenarios, like identifying intruders based on historical behaviours
• Personalised education: AI tutors process student interaction videos, remember progress and misconceptions over time, and deliver tailored lessons, such as adapting math explanations from weeks of observed struggles.

Read the paper: Seeing, Listening, Remembering, and Reasoning: A Multimodal Agent with Long-Term Memory.

Wrestling with the 'Wild West' of Large Language Models (LLMs)?

While LLMs are poised to redefine business, the crucial 'secret sauce' of reinforcement learning (RL) has become a labyrinth of conflicting advice and unproven 'tricks', leaving organisations confused and hindering true progress.

Today we cut through the noise with groundbreaking research that meticulously deconstructs the RL landscape for LLMs, bringing much-needed rigour and clarity.

Discover why:

• A 'minimalist combination' of just two simple techniques – dubbed Light PO – dramatically outperforms complex, multi-component algorithms like DRPO and GRPO. This revelation alone could redefine your AI strategy, leading to more efficient development and superior model performance on complex reasoning tasks
• The effectiveness of key RL methods like advantage normalisation and clipping depends entirely on your model’s existing capabilities and data structure, not a 'one-size-fits-all' approach. This nuanced understanding is critical for avoiding costly missteps and ensuring robust, adaptable LLM development
• Transparency and collaboration are highlighted as the ultimate accelerators for future AI innovation.

Understanding this research will not only clarify your internal LLM initiatives but also equip you to advocate for the open-source principles vital for broadly beneficial progress across the industry.

Tune in to gain a strategic advantage in the LLM era. Move beyond the hype and guesswork; understand the foundational principles that will truly unlock reliable, intelligent AI for your business.

This is an essential listen for any business leader navigating the complex, yet transformative, world of advanced AI.

Businesses are looking at vibe coding all wrong. They're trying to brute force products using 0 engineers, all vibe coding.

It's a bugger's muddle. You can't win. AI doesn't understand you, your customers, or your organisation.

But vibe code has an ace up its sleeve.

Creating prototypes is how to shave weeks, months, or even years, from your product development roadmap. No more product and engineering clashes. Build, test, review, progress.

Here's a fantastic discussion about how to make it work for your business.

Inspired by:

https://ordep.dev/posts/writing-code-was-never-the-bottleneck

https://www.youtube.com/watch?v=i44jQvcDARo

That journalist is me, your host and producer of AI Today - Dave Thackeray.

I was approached by a researcher from the data labs at London School of Economics who wanted to find out how writing had changed in the AI era.

We used to write logically, emotionally. But now logic is the domain of the machine, we need to work harder than ever on our EQ - emotional intelligence - to resonate deeply with our reader.

I've been writing alongside AI for years. And I believe that this harmonious relationship pays dividends - whether you're a professional writer, or simply want to communicate with impact.

Hope you enjoy the show - and the loaf was delicious!

Read the transcript here.

ASI-ARCH is an Artificial Superintelligence (ASI) that's a game-changer for AI research.

Like a tireless super-scientist, it has autonomously invented 106 ground-breaking AI 'brains', unearthing surprising design principles far beyond human intuition.

Crucially, this proves AI innovation can now scale directly with computing power, not human effort.

This unlocks the immense, practical potential for self-accelerating AI development, promising an era where AI gets better at building itself, at an unprecedented pace.

Read the paper at arXiv.