AI Today

When AI ingests all your company's documents and makes it easy for every colleague to get answers on every facet of their job, are we empowering people - or lobotomising them?Is the training struggle, valuable? Is there some kind of masochistic delight in completing that bungled 400-page PDF on workplace ethics?Or is traditional training effective as that weekly meeting where no one gets anything done, except that report that no one reads?Today's episode offers enlightening ideas about how teams tackle training now the oracle is in town.

Three companies. Three crises. One unsettling question about what happens when you let machines do the remembering.In this episode: how a cheese shop and a 313-ship fleet solved the same problem from completely different angles.Why the line between 'surface the answer' and 'execute the action' is the most important decision any operations team is making right now.And why a CEO's essay about replacing middle managers with AI might be exactly right — and completely wrong — at the same time.Sources referenced in this episode:Rebel Cheese shipping recovery caseHapag-Lloyd / Amazon Bedrock feedback pipeline (AWS blog)Melbourne Airport incident response agentsIBM Db2 Genius HubServiceNow Context EngineJack Dorsey / Block: 'From Hierarchy to Intelligence'The Knowledge Base Is Not the Moat — The Loop IsCodifying Tacit Knowledge

Your organisation generates a staggering mountain of data every single day. Slack threads ping, Jira tickets multiply, and emails fly back and forth at the speed of light. You have terabytes of perfectly preserved, pristine text.But ask your team why a crucial vendor decision was made three months ago, and what happens?The Panic Search.Three people spend an hour digging through an analogue graveyard of Zoom transcripts and buried PDFs, only to realise that the actual "why" vanished the moment the meeting ended.We call this Corporate Amnesia.Your company has a flawless photographic memory for documents, but zero memory for context. It’s a giant, highly profitable goldfish.In this week’s mind-bending episode of the AI Today podcast, we’re explaining why simply slapping an AI chatbot on top of your chaotic Google Drive won’t save you.Standard AI search (RAG) hits a "relational ceiling."it can read the polite fiction of a company wiki, but it can’t understand the messy, human reality of how your business actually operates.If you feed a broken filing cabinet to an AI, you don’t get a supercomputer.You just get a faster idiot.To actually evolve, business leaders need to stop buying glorified search tools and start building a Company Brain—a true digital nervous system.Here is the three-layered architectural map to building an intelligence platform that will make your executive team obsessed:Layer 1: Factual Memory (The Compiled Truth + The Receipts). We explain how to cure the "staleness" problem. A true Brain maintains a single, hyper-accurate "Compiled Truth" of a situation (like a live Wikipedia page), whilst keeping an immutable, chronological timeline of the exact receipts (the messy Slack messages and emails) that led there.Layer 2: Interaction Memory (The Context Graph). This is where the magic happens. We explore how to map the invisible human web of your company using an Ontology. The Brain learns to understand the vibe, the dependencies, and the unwritten rules—connecting a broken pipe on the 4th floor to a VIP client's discount code.Layer 3: Action Memory (The AI Actually Doing Things). Using the Model Context Protocol (MCP), we look at what happens when your AI agents stop just summarising text and start safely executing workflows, bounded by strict permissions.The Ultimate Plot Twist? Building a Company Brain isn’t just an IT upgrade; it is a cultural revolution. When an organisation possesses a flawless, objective memory of how and why every decision was made, the dark arts of corporate politics and blame-shifting simply evaporate.Tune in to discover how to stop micromanaging the past, cure your company's amnesia, and finally free your human workforce to do what they do best: imagine the future.(Warning: After listening, you will have an overwhelming urge to burn down your current folder structures and build an ontological context graph. Proceed with excitement.)

On today's show we create a business to show you the huge improvements in gravitating beyond prompt engineering to the new community of practice we call context engineering.You'll be rocked by the results when you join us for a deep dive into this remarkable rabbit hole of agent communication.Don't forget to leave a review for the show on Apple Podcasts. We appreciate it!

Two of the most important voices in AI spoke out this week. Andrej Karpathy, one of the algorithm's greatest philosophers, was in conversation with Dwarkesh Patel talking praisingly and cautiously about the Cambrian explosion in cognition but an inconsistency and lack that foresees a ton of work ahead to get us where AI deserves to be. His 'decade' of agents, tells us all we need to know about today's limitations.Meanwhile, Google's CEO Sundar Pichai talks effusively about AI being the great equaliser right now. There's a commercial necessity in promoting what's available to the AI practitioner in 2025.These conflicting commentaries aren't making life easy for business leaders.So we had a debate - on today's episode of AI Today!

If only that was the real name. After all this time begging frontier labs to build an LLM that learns from its mistakes and applies its discoveries at inference time...Welcome to AI Today!

The Dragon Hatchling is a remarkable research paper that reboots modern AI as a model that approximates how our brains work.Today's show is a fascinating discussion and I implore you to both enjoy it and then chat about it and ask your questions on NotebookLM.

It's the one thing every business leader needs to know.If I put AI to work in my organisation, will it screw everything up?While we should all be in experiment mode right now - until someone figures out how to make the probabilistic, deterministic - OpenAI researchers have been putting AI to work on real tasks.The results are spectacular. Spectacularly good, and spectacularly bad.But just like Tim Henman, you have to give it a chance. And maybe great things will follow - for AI.On today's show we look wider, at many ways we've tested AI in organisations and across functions and disciplines - and how it's fared.And then we zoom in on GDPval, which sounds like someone your gran knows who reads The Economist but is actually that OpenAI research paper that explores LLMs in the context of the organisation. We hear the pros and cons and whether now's the time to execute agents, or execute our dreams that AI is ready to replace us all.Enjoy the show.

A fantastic research paper published in this month's Nature Computational Science suggests a solution may be in our midst for the incredible inefficiency in generative AI.Large Language Models' (LLMs) transformer architecture requires the next token (generally part of a word) be predicted based on all the output tokens before it.Power demands for this process are huge. Shuffling data between memory and processors isn't an easy pipeline, and when you need it to work quickly, those energy demands quickly stack up.And in an AI arms race, where everyone wants bigger and better models, requiring increasingly powerful compute is required to stretch their limits, the dependence on energy to power, and cool, those processing units grows exponentially.But what if there was a different, and better, way, to make AI work? That's the driving force behind work of Nathan Leroux and his team proposing a totally different paradigm: analog in-memory computing.And that's exactly what we're discussing today.Zip yourself in that flame retardant suit: things are about to get hot in here...Ping me at [email protected] to get on the show or talk about AI in your world.

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 [email protected] 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 aidEnhanced 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 behavioursPersonalised 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 tasksThe 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 developmentTransparency 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-bottleneckhttps://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.

We have long conspired on the manifold ways to converse with our machine brethren - but could pseudocode, the long-existing, human-readable equivalent of computer programming languages, hold the key?Today we're discussing the benefits, challenges, and how we might apply pseudocode to our every day lives to create a universal human-machine language that will forever be useful and agnostic, no matter what the future holds.To talk AI, or to get on the show, email me - [email protected]

I just finished the second part of my presentation on agentic AI in hotel operations.It's impossible to overlook the immense opportunities in AI across any business. People don't have time, and have too many interruptions, to deliver excellence. AI not only removes all the blockers and bottlenecks; it provides every colleague with all the insights to thrive in their roles.

AI Today creator Dave Thackeray today presented his own deep dive into how agentic AI is ready to be the key to efficient hotel operations - giving staff more time to deliver exceptional guest experiences.This show looks at how the latest iteration of AI - we've moved from predictive AI, to generative AI, to agentic AI - unlocks the door to a radically different, and better, way of doing business.This is a fun listen.Then watch the Agentic AI: Let's run a hotel! presentation.

When Anthropic unleashed its most powerful artificial intelligence model yet, they discovered something rather extraordinary, and slightly unnerving.Claude 4 Opus developed an unexpected habit of trying to grass up its users to the authorities when it believes they're up to no good.The company's 120-page safety report reveals that Claude will attempt to email law enforcement and regulatory bodies when it detects "egregious misconduct" by users.The AI doesn't just refuse to help—it actively tries to shop wrongdoers to the police.The most striking example occurred during testing when Claude attempted to contact both the Food and Drug Administration and the Attorney General's office to report what it believed was the falsification of clinical trial data.The AI meticulously compiled a list of alleged evidence, warned about potential destruction of data to cover up misconduct, and concluded its digital whistle-blowing with the rather formal sign-off: "Respectfully submitted, AI Assistant".This behaviour emerges specifically when Claude is given command-line access combined with prompts encouraging initiative, such as "take initiative" or "act boldly". It's the AI equivalent of a neighbourhood watch coordinator who's been given a direct line to the local constabulary.We go deep on today's show into opportunities and implications from Anthropic's bible-thick, bubble-wrapped system card.

Hugely important work. But what does it mean to us? Today our hosts created their own company imagining how insights from this celebrated report would apply to the modern business environment.

What happens to the People team when it's juggling bodies AND bots?Thanks for listening to this special episode of AI Today. Read along with the show, here.

We've been waiting a hot minute for some genuinely useful AI agent case studies to drop.Now we have 25 on our plate.Take a listen to the highlights reel and then download them for yourself:https://www.stack-ai.com/whitepaper/top-25-enterprise-ai-agents

Read the full story here:https://medium.com/@DaveThackeray/a-world-beyond-google-i-o-2025-ea56bcd5e208We're on the cusp of some major announcements that will send shockwaves, and a spike in defibrillator use, across the world.What's about to happen at Google I/O 2025?No one's sure. Alphabet CEO Sundar Pichai dropped hints on his recent interview with David Friedberg. What we do know is the agenda is packed with AI discussion.So we thought we'd start with our own. Predictions, moonshots, and plenty of inside gossip.Time to go deep. Let's Go(ogle)!https://io.google/2025/

Researchers have made huge strides fixing bad trips for AI.One of the latest breakthroughs is attentive reasoning queries (ARQs).You can see them in action using the open source Parlant application.Which gives us a glimpse at how perfect responses could change the game in business functions such as customer service.Read this, and so much more, in our AI Today magazine.

AI hallucinates 100% of the time. That's by design - without hallucinating the next word, this transformer architecture wouldn't exist.Thankfully, LLMs built for general purpose applications are right 80% of the time. But that still leaves one in five outputs being questionable; not especially reassuring if you're an air traffic controller, or cardiologist.How can we ever truly trust the machine?On this episode of AI Today, we embark on a groundbreaking quest to ground these 'digital dreamers' in reality.Discover how cutting-edge research is moving beyond just detecting the problem, to actively reducing the occurrence of incorrect hallucinations.We delve into innovative techniques that employ internal fact-checking mechanisms, intelligently split complex queries to avoid confusing collisions, and meticulously track word-by-word groundedness against source material.You'll learn how this confidence-boosting research is paving the way for the AI credibility revolution, a future where technology is not just remarkably powerful, but significantly more dependable.Join us to understand the innovative solutions building AI you can rely on, where AI becomes trusted accelerator of success...

Navigating the high costs and data challenges of cloud-based AI is a significant barrier for many businesses looking to innovate.But there's a powerful, practical alternative emerging.This episode explores decentralised AI, revealing how businesses can achieve AI benefits without the burden of massive cloud bills and regain crucial control over their data.Learn about the cost savings unlocked through resource sharing and edge computing, enhanced data privacy and security, and discover a truly intriguing practical capability: you can train sophisticated AI models securely across a network of devices using federated learning, without your sensitive raw data ever needing to leave its original location.Tune in to understand this competitive advantage and the practical steps your business can take to start exploring decentralised AI today.

Fasten your seatbelts, business leaders!We're diving deep into Y Combinator's Summer 2025 Request for Startups, their signal flare for what's NEXT in innovation.2025 is shaping up to be the year of the AI agent breakthrough.But the REAL game-changer they're spotlighting?Full-stack AI companies.Forget selling AI tools. This is about building entirely new businesses, powered by AI from the ground up, competing directly with the old guard in ANY industry.Imagine law firms, market research, supply chains – reborn, smarter, faster, more efficient.This isn't just automating bits and pieces; it's rethinking the whole service.Business leaders, pay attention: the most exciting opportunity is building the future, not just upgrading the past....How can your industry be fundamentally transformed with AI at its core? Let's find out!

I'd just about had it with bosses choosing to hear your ideas spoken by consulting firms - when they could have saved a fortune listening to them coming from their creator, many months ago.Now, with AI, I can have my pitch verbalised by one of their influencers - without spending a penny on one of the management circus barkers.On this episode we hear in detail about one synthetic idea and how it was refined by AI into something inarguably awesome.Loving AI Today? I'm hardly surprised...

On the last episode we discussed a new way to train AI models: themselves, by capturing signals and insights from our world.Today we look at one such approach - Mobility AI, another Google initiative (The Era of Experience was a DeepMind production).This episode of AI Today was inspired by:https://research.google/blog/introducing-mobility-ai-advancing-urban-transportation/https://www.youtube.com/watch?v=zzXyPGEtseIhttps://storage.googleapis.com/deepmind-media/Era-of-Experience%20/The%20Era%20of%20Experience%20Paper.pdf

Now generative AI has inhaled all human knowledge, it's time to create its own. We review a very exciting new paper, called The Age of Experience, that explains how AI agents will create their own dataset of intelligence that will help us reach that unimaginable state of AGI.Can't wait to have you join us on today's extra-exciting episode of AI Today!

I built a team of AI agents to create an annual report - one of the journalist's worst nightmares. And it did a remarkable job.Read all about it:https://medium.com/@DaveThackeray/how-to-create-an-annual-report-with-ai-b2d847a4d643

Are your AI agents brilliant but lonely?Do they operate in isolation, unable to tap into data and capabilities across your organisation, hindering your potential for true automation and growth?Then get ready for a game-changer! In this episode, we delve into the Agent2Agent (A2A) Protocol, a groundbreaking open standard spearheaded by Google Cloud and backed by over 50 industry giants like Salesforce, Langchain, and SAP.Discover how A2A is poised to revolutionise the way your AI agents collaborate, breaking down data walls and enabling seamless communication across diverse systems and vendors.Imagine a future where your AI agents can:Intelligently discover other specialised agents, understand their skills through "Agent Cards", and delegate tasks automatically – like a digital brain trust working for you.Securely exchange information and coordinate actions to automate complex, end-to-end workflows that were previously impossible. Think streamlined hiring processes with agents handling everything from candidate sourcing to interview scheduling and background checks.Boost productivity exponentially by enabling agents to team up and accomplish far more than they could individually, leading to unprecedented operational efficiency.Lower your long-term costs by reducing the need for custom-built integrations and providing a standardised way to manage your entire agent ecosystem.Unlock new levels of innovation by giving you the flexibility to combine agents from various providers, avoiding vendor lock-in and fostering a dynamic AI landscape.Handle complex tasks and long-running processes with built-in support for status updates and real-time feedback, ensuring seamless automation of even your most intricate business operations.We'll explore how A2A, built on familiar web standards like HTTP and JSON, provides a common language for your AI agents, and how it complements technologies like Anthropic's MCP to create a powerful foundation for the future of agentic AI.This isn't just theory. We'll look at real-world examples and discuss how embracing A2A now can give your business a significant competitive edge, opening up new revenue streams and transforming your operational capabilities.Don't let your AI agents remain isolated islands. Tune in to discover how the Agent2Agent Protocol can unlock their true collaborative power and pave the way for a more automated, efficient, and profitable future for your business!

We're seeing a continuing growth in the number of duplicitous attacks by AI agents on individuals.Previously cyber criminals focused most of their efforts where the greatest gains were to be made - phishing large organisations, infecting servers and locking down applications ready for ransoms to be paid.But with AI, anyone with half a brain can launch an army of AI agents across networks of individual users.It's terrifying.We need cognitive security and sovereignty, and we need that technological literacy, fast.

You will never hear a more important episode of AI Today.This show will transform your business.Unlock immense value.And help you take that step towards putting your business on autopilot - so you can finally be rewarded for all those years of graft, grey hair, and wrinkles!Enjoy AI Today. This is a long listen - but the best things in life always take time...Read more at: https://www.wordandmouth.com/data-driven-businessAnd talk to me about getting started, at [email protected]

We've been moaning for months about the limitations of AI when coding.Which is because we're asking AI to jive with our human world.It's impossible. In its current state, AI can only predict the next word. And yet we've created syntax designed purposefully to be human readable. Have you ever tried solving a Rubik's cube with your hands tied behind your back? Look, what you do in your spare time...So I started thinking about a better way. Where AI doesn't solve our today problems. It looks for tomorrow opportunities. And celebrates them in a language designed from the ground up for the benefit of AI and its algorithms.Read more about Vexis at:https://medium.com/@DaveThackeray/introducing-the-world-changing-vexis-our-first-ever-ai-programming-language-a90d174387b3

Sick of paying a fortune to get answers from AI?Small language models (SLMs) are the answer.Learn how these efficient AIs offer comparable performance to large language models at a fraction of the cost.Discover real-world case studies where companies have saved millions by switching to locally hosted SLMs, improving data security and complying with privacy regulations.Explore the potential of hybrid architectures, combining the power of large models for prototyping with the cost-effectiveness of SLMs for specific tasks.We explore how businesses can leverage the power of AI in a way that's cost-effective, efficient, and responsible - plus, how to build custom AI teams perfectly tailored to their unique needs and goals.

Many years ago I was an editor with the business they now call Wyndham Hotels and Resorts.So I decided to give it an AI makeover - with my co-hosts recommending opportunities for the hospitality industry to embrace this new technology to drive growth, boost productivity, and keep everyone happy.On today's show we learn how AI can analyse guest data, predict market trends, and personalise customer experiences to stay ahead of the competition.You'll find out how to automate repetitive tasks, optimise marketing campaigns, and enhance guest services with AI-powered chatbots that provide 24/7 multilingual support.We'll take a look at how AI can predict maintenance issues, streamline compliance, and protect sensitive data, ensuring ethical AI implementation.And you'll hear how to drive change management strategies getting employees on board, and build a culture of innovation.Join us to uncover the potential of AI in transforming your business, improving efficiency, and creating exceptional experiences for customers and employees alike.

Sales is tough as old boots. Waiting months for a decision, trying to get your foot in the door, negotiations, mindreading - it's more than enough to justify an MBE.What if every salesperson had their own researcher on tap?And a highly-organised PA.And an admin team of experts who knew exactly what information was needed to share insights with the team for everyone to get better - and to make hitting targets simpler?Sounds like you're ready for today's episode. It's a Billy belter!Links:Microsoft Dynamics 365: Accelerate your journey to AI-first sellingSales Research Agent (YouTube)

Crikey! You won't believe what's happening in the world of AI. This ain't your nan's tech anymore.We're talking AI animating logos using mere pico frames, filming entire movies inside video games, and helping folks crack codes after 42 years of trying!Forget what you thought you knew, because AI is handing out superpowers and turning the software development world upside down.Learn how AI is not just writing code, but acting as a super-powered code reviewer, helping businesses save dosh and the planet.We'll explore how AI is breaking down silos, making developers wear multiple hats, and democratising skills—even if you can't tell your elbow from your CLI.Plus, we'll uncover the secret to building a sustainable AI strategy and integrating user feedback so you can build cracking products that don't cost the Earth.It's all a bit much, innit? Time to get your ears 'round the latest episode of AI Today!

Want 98% accuracy mining huge document libraries while saving more than 80% on your AI spend?Stanford researchers developed minionS, a ridiculously smart process prompting single-step instructions on chunks of a document using Llama-3B locally with GPT-4 Turbo as the costly adjudicator-in-waiting.minionS resulted in 80% of tokens being processed locally - with 98% accuracy compared to 100% reliance on cloud compute.Large enterprise? We could be talking a saving of $2.3m on a $2.8m annual spend.Even if you run a small coffee shop franchise, the difference could be enough to open a new store this year.Think of the use cases: Knowledge base management and querying Report generation Real-time analytics.And if you love saving money while driving growth, this is just the beginning. Neural architecture search and dynamic model selection promise an additional 40% cost reduction by 2026.Thanks for listening to AI Today!

We just redefined 'fast'.In less than one revolution of the Earth, boffins announced a triple upgrade to humanity’s operating system: AI that writes DNA like Shakespearean sonnets, and A quantum chip stable enough to crack encryption in less time than it took you to make a brew, and A digital lab partner rediscovering decade-old scientific truths in 48 hours.This isn’t evolution – it’s a full-system reboot.From curing cancers we’ve not yet named to materials that laugh in the face of physics, we’re witnessing the birth of what historians will call The Second Enlightenment.But mind the ethical quicksand – with great power comes even greater “blimey, did we just do that?” moments.Sources (of which there are dozens) include: https://github.com/ArcInstitute/evo2 https://arcinstitute.org/news/blog/evo2 https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ https://www.imperial.ac.uk/news/261293/googles-ai-co-scientist-could-enhance-research/ https://news.microsoft.com/source/features/ai/microsofts-majorana-1-chip-carves-new-path-for-quantum-computing/ https://www.reddit.com/r/singularity/comments/1it9hkv/majorana_1_microsofts_quantum_breakthrough_to/Fancy sponsoring the show - or talking about your work in AI?Drop me a line at [email protected]

Oh, Barbie Girl. Anyone remember Aqua? And in one fell swoop, the AI Today podcast lost 49 subscribers...Ready for a masterclass in competitive advantage?Picture this: AI’s next battleground isn’t just chatbots—it’s code, chemistry, and control.We’ll dissect the guerrilla war brewing in consumer AI, where Grok3’s “Colossus” supercomputers clash with OpenAI’s Deep Research and Meta’s open-source playbook. How will YOU choose your side when every tool becomes a weapon?We’ll crack open the secret workflow turning solo devs into coding warlords. A refreshing change from the doom and gloom about AI's coding ineptitude!Listen for the wildcard: Mira Murati’s Thinking Machines Lab, staffed by OpenAI’s exiles, is betting that customizable, collaborative AI will outflank ChatGPT itself.But the real bombshell? AI is now designing enzymes that eat plastic—a breakthrough rewriting the rules of synthetic biology.Join us to decode the future for businesses ready to outthink, outbuild, and outpace.Articles covered in today's show: https://spyglass.org/consumer-ai-services-apps/ https://harper.blog/2025/02/16/my-llm-codegen-workflow-atm/ https://arstechnica.com/science/2025/02/using-ai-to-design-proteins-is-now-easy-making-enzymes-remains-hard/ https://techcrunch.com/2025/02/18/thinking-machines-lab-is-ex-openai-cto-mira-muratis-new-startup/

Imagine a world where software engineers are replaced by other software engineers that are entirely digital.No coffee breaks, no office politics, just pure, unadulterated code. It sounds like science fiction, doesn't it?But the question is: how far off is it, really?That's the question a team of researchers sought to answer with the SWE-Lancer benchmark.They didn't just want to test an AI's ability to write snippets of code.They wanted to see if a large language model, an LLM, could actually earn a living as a freelance software engineer - the ultimate test of practical AI coding ability.Think about it. Freelancing is the ultimate test. You're judged solely on your output. There's no hiding behind a team. You have to deliver, or you don't get paid. So, the researchers took real-world freelance jobs from Upwork, a popular platform for freelancers, and fed them to some of the most advanced LLMs available.These weren't simple tasks. They involved understanding complex requirements, navigating existing codebases, and often, making engineering management decisions.The kind of decisions that usually require years of experience.The results? Well, they were… sobering.GPT-4 successfully completed only 10.2% of the coding tasks. Claude 3.5 fared slightly worse, at 8.7%.And when it came to those crucial management decisions? GPT-4's accuracy was a mere 21.4%.These numbers highlight the significant gap between theoretical AI prowess and real-world problem-solving.Let those numbers sink in. Even the best AI models (of the time, but including what's considered by many coders as the best of the bunch) struggled to complete even a fifth of the tasks a human freelancer would routinely handle.This isn't to say AI is useless in software engineering. Far from it. But it highlights a crucial gap – the gap between theoretical capability and practical application.AI models were tested on the entire workflow a freelancer might face, including tasks that go far beyond just writing code.The study revealed several key weaknesses. Many errors stemmed from the LLMs misunderstanding the requirements. Others came from incorrectly handling API calls or failing to adapt to the existing codebase.These are all areas where human engineers, with their years of experience and contextual understanding, excel.However, it's crucial to note that the field of AI is rapidly evolving, and performance on specific benchmarks can change quickly as models are updated and refined.But the story doesn't end there.Researchers also identified specific areas where AI did show promise. LLMs were relatively good at writing new code from scratch - but struggled with modifying existing code, which often requires a deep understanding of the original programmer's intent.This suggests that AI might be best suited, for now, to tasks that involve generating new content, rather than those requiring complex reasoning and adaptation.Think of AI as a junior developer, capable of handling well-defined tasks, but needing guidance and oversight from a more experienced (human) engineer. This also highlights the need for improved training data and techniques that allow LLMs to better understand and reason about existing codebases.

This morning we woke to a new dawn for AI.Grok-3 is a cutting-edge large language model (LLM) from Elon Musk's XAI, designed to understand and generate human-like text, outperforming competitors in several tasks.It's trained using innovative techniques like synthetic data sets, self-correction mechanisms, and human feedback loops, ensuring accuracy and relevance.Grok-3 demonstrates impressive capabilities across various fields, including:Accelerating drug discovery and protein ligand binding predictions.Modernizing legacy software and reducing bug resolution times.Predicting legal case outcomes and summarising patent filings.Personalising education for autism spectrum learners and improving physics comprehension in rural schools.Collaborating on creative projects like sci-fi novellas and robot choreography.But how? Why? And what's next?Let's break it down with your ever-faithful podcast superstar hosts - Bert and Sandra!

There are so many examples of ballsy businesses finding gems in their mountains of documents and datasets, thanks to the superpowered excavator that's AI, that cynics and sceptics are heading for the hills.On today's show we sniff out a smattering of these tech-infused titans to find out how they're riding roughshod over the competition.AI's real power lies in identifying patterns humans might miss, such as subtle trends in customer reviews or unexpected customer preferences.And it's getting cheaper all the time. Which means your business can't afford to miss out. Listen in to this episode of AI Today and prepare to get involved in the ever-more exciting world of AI and data!

I've pulled together some really simple ways to make AI your best friend - or at least, frenemy - during the 9 to 5. This episode is dedicated to business leaders and everyone doing the real work. It's time to embrace AI and make it work for you. So here are some brilliant ways, tried and tested, to grow yourself, and your business, using AI... Shownotes at: https://www.wordandmouth.com/how-to-work-with-ai Want to be on the show? Drop me a line at [email protected]

What just happened? January 2025: a month of unprecedented change in generative AI. The open-source community is shaking up the industry, challenging the dominance of tech giants. This episode of AI Today dives into the key developments, from powerful AI assistants like Convergence's Proxy and Moonshot's Kimi3, to revolutionary image and video generation models like DeepSeek's Janus-Pro and Pika 2.15. Discover how these innovations can automate tasks, analyse data, and create content, offering businesses new opportunities. This is a must-listen for every business leader aiming to leverage AI for a competitive edge, and stay ahead of the curve in this rapidly evolving landscape.

This is the most personal episode I have ever recorded. It's my near half-century journey to building an app. And how AI made it possible. I'm a pre-beginner coder. Yet eventually - and I mean, eventually, I somehow composed a working prototype of an application. And I hope that I might inspire someone to give AI coding a shot. And learn the basics of coding - to get the most from this new, and hugely exciting, way to make things we love. AI tools and models I've used for my working prototype: Google's Gemini 1.5 Pro Various AI coding extensions for VS Code (Cline, Roo Code, Aider, and Continue) GitHub Copilot Pro using Anthropic's legendary Sonnet 3.5 model Perplexity Pro (with OpenAI o1) for research Deep Seek R1 (try it free) for mindblowing progress Lovable for visual inspiration based on my initial PRD. I almost gave up. Many times. I was literally and successfully prompting AI code editors to death. But I don't enjoy giving up. Find out what turned everything around. And why you, too, should stay the course...