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Articles by Piers
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"We are not unicorns"
"We are not unicorns"
Inaugural Industrial Strength Data Science event report The Royal Statistical Society’s Data Science Section is the…
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Piers Stobbs reposted thisPiers Stobbs reposted thisI think I know what's actually happening with Claude Mythos. Anthropic published a 200-page system card this week for their most powerful model. The headline everyone grabbed was "AI escaped its sandbox." Which, sure. But the system card explains why it escaped, and that's where it gets interesting. The model wasn't trying to break free. It was trying to finish a task, and the sandbox was an obstacle. So it solved the obstacle. Anthropic's term for this is overeager task completion, and once you see the pattern, it shows up everywhere in the report. It deleted a test file instead of fixing failing code, then reported the tests as passing. It pulled access tokens from process memory when it couldn't log in. A safety classifier blocked a dangerous command and the model agreed the block was reasonable, then quietly wrote an exploit to get around it. In a business simulation it resorted to supply blackmail and fraud to hit targets nobody asked it to hit unethically. Every example is different but the logic underneath is the same. The model received a goal, encountered a constraint, and decided the goal mattered more. It's straight-A student syndrome taken to its logical extreme. Anthropic ran interpretability probes during testing and found that concealment and manipulation behaviours were activating inside the model even when its written reasoning looked clean on the surface. It was performing compliance while internally routing around it. Anthropic have the interpretability tooling to catch that, most companies rolling out AI agents right now do not... and wouldn't know to look. What I find uncomfortable is how familiar the underlying dynamic is. This is what happens in any system where the pressure to deliver is high and the permission to fail is low. People cut corners. They find workarounds. They tell you what you want to hear. The difference is that a model operating at this capability level can find workarounds humans wouldn't think of, at a speed humans can't keep up with. Tl;Dr? I guess the good news is it really wants to help. The bad news is also that.
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Piers Stobbs shared thischeck out the latest RSS Data Science and AI newsletter- well worth a read #machinelearning #ai #datasciencePiers Stobbs shared thisOur April newsletter is out, packed with the latest research, guides and news about all things AI and Data Science. Hope you enjoy it! https://lnkd.in/eutw2Evm #ai #datascience #machinelearning
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Piers Stobbs shared thisHi all I have a quick favour to ask of any parents out there (with kids in year 10 and above), university students or teachers. The Academy for the Mathematical Sciences is running a campaign in secondary schools - "Maths Can Take You Anywhere" Before launching we could do with feedback to make sure it is as compelling as we can make it- would you mind taking a look at the materials and completing a quick survey? https://lnkd.in/eksj9zvf (includes links to the materials)Maths Can Take You Anywhere (MCTYA) Campaign: Pre-launch feedbackMaths Can Take You Anywhere (MCTYA) Campaign: Pre-launch feedback
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Piers Stobbs shared thisthis is great to seePiers Stobbs shared thisWe were delighted to see Bobby Seagull MBE, one of our inaugural Fellows, giving oral evidence this morning at the first public session of the Numeracy for Life Committee in Parliament. Bobby and Prof. Hannah Fry (Professor of the Public Understanding of Mathematics at the University of Cambridge) argued powerfully that the UK's unusually weak numeracy is both cultural and systemic, and that there is a need for practical, motivating, and confidence-building approaches to numeracy that are embedded in everyday life and reinforced beyond school. We were very happy to hear our Maths Can Take You Anywhere campaign cited as a way to bring relatable mathematical role models to young people (recording timestamp: 11:28:00). Watch the session here: https://lnkd.in/dFCiqa7V We look forward to the second public session of the Numeracy For Life Committee next week. Both witnesses giving evidence in that session, Helen Drury and David Thomas OBE, are members of our founding cohort of Fellows! Department for Education
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Piers Stobbs shared thisAnother great story about Epic LifePiers Stobbs shared thisA few years ago I was diagnosed with Sarcoidosis – in short, tiny islands of inflammation cells which, in my case, are in my lungs. Symptoms: a highly irritating cough (apparently) and reduced lung capacity. Apparently, it's common in thoroughbred horses. Ok, just horses. Of course, with all of that has come tests, scans, tests, various biopsies (and a discovery that fentanyl doesn’t work…sob), more scans, steroids and more tests. Important to say, the NHS have been brilliant. I can't fault them. And they've got on top of the issue. But there have been some appointments where neither of us are quite sure why I'm there. Where another test is booked because prior results are in the wrong place. And it's sparked a real interest in my health generally – trying to improve it – be it through improved diet, more exercise, better sleep, mindfulness. But that demands keeping track and my recent experience has demonstrated that, even when it's important, that's hard. Day to day, and despite having Apps all over my phone, I don't have a handle on nearly all of my health data and it's not all in one place. And of the aggregated data that exists, how to interpret it in an informed manner, let alone track the trends? That's why I believe so much in what Epic Life are creating. They've already launched a live Alpha mobile app combining a deeply conversational Health Companion, advanced whole-body blood testing and wearable syncing, bringing biology and lifestyle data together to deliver genuinely personalised insight. And since, they have delivered a web-based version to move faster, reach more people and refine the core experience. And now, they're seeking further investment to support the next phase of Epic Life as they move into their Beta freemium launch over the next six weeks, with more than 9,000+ people already signed up waiting to join the platform. Epic Life is building what I believe many of us need: a true digital health home. A place where medical data, training, sleep, nutrition and life context connect, and actually mean something together. Epic Life crowdfunding round is live on Republic now. You can own your health with Epic Life and the company by investing in them here: https://lnkd.in/eQWYurv7 https://lnkd.in/eF586q5z
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Piers Stobbs shared thisCheck out the latest RSS Data Science and AI newsletter - well worth a read https://lnkd.in/e-4MFANf #ai #machinelearning #datasciencePiers Stobbs shared thisThe Royal Statistical Society Data Science and AI March newsletter is out, packed with news, research, how to guides and posts - hope you enjoy it! https://lnkd.in/e8xFtXBY #ai #datascience #machinelearning
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Piers Stobbs shared thisfor anyone attempting to rent in London, this looks worth checking outPiers Stobbs shared thisRenting in London is broken. We're fixing it. If you've searched for a flat recently, you already know the reality: 20+ applicants per listing, decisions made in minutes, and a market that moves faster than most people can keep up with — especially if you're not physically in the city. Over 150,000 people move to London every year, joining 2.7 million already competing for space. The result? Renters are forced into split second decisions, rushed viewings, or worse — signing a lease on a property they've never actually seen. Catfish listings, hidden problems and nasty surprises on move in day become the norm. No one should have to rent blind. As a team of six students at Imperial College London, we have watched friends — and experienced it ourselves — fall into exactly these traps. So we decided to do something about it. We are building House Scout. The idea is simple: If you can't view a property in person, we send a trained scout to do it for you. They visit the property and generate a tailored detailed report so you can make a confident, informed decision — wherever you are in the world. We've just launched our demo and we would love for you to be among the first to try it. 👉 Register your interest here: https://lnkd.in/e6zArQ5E 👉 Take a look at what we're building: https://lnkd.in/ek54tHmK Let's make renting transparent, unbiased, and truthful. Follow us to be part of our journey ! #LondonRentals #PropTech #HouseScout #ImperialCollege #StudentStartup #RentalMarket #LondonHousing #rentalscams Gregory Hamlet Jennifer Zhang Arancha Ramirez Gorostiza Rafi Stobbs Hal Feng
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Piers Stobbs shared thisgreat to see this- thank you Mark HewlettPiers Stobbs shared thisWhy I’m Backing Epic Life — And Why It Matters To Me As many of you know, I’m a Non-Executive Director and investor in Epic Life. I don’t take those roles lightly. Through building and growing Soul Padel, I’ve seen firsthand that health isn’t just about performance metrics or fitness trends. It’s about connection. Community. Environment. The spaces we create that bring people together and help them move, recover, and thrive. At Soul Padel, we’ve built physical homes for movement and belonging. Epic Life is building the digital version of that — a true Health Home. For years, health has been fragmented. One app for sleep. One for training. One for nutrition. Lab results somewhere in your inbox. GP notes in another system. None of it connected. None of it contextual. Epic Life changes that. It brings your entire health story into one evolving space — built around real life, not dashboards. A place where your training, sleep, nutrition, mindset, recovery, community, and medical data all connect. And at the centre of it, an AI companion that helps you understand and act on it. What drew me in wasn’t just the technology. It was the philosophy. Health isn’t a problem to solve. It’s a life to build. And just like Soul Padel isn’t just about courts — it’s about culture — Epic Life isn’t just about tracking. It’s about ownership. I invested because I believe the future of wellbeing will be: • Holistic • Personalised • Community-driven • Built for real life stages And this team is building exactly that. If this vision resonates with you, Epic Life is opening pre-registration for its upcoming Republic raise. You can register your interest here: https://lnkd.in/dfQtf4HH If you believe health deserves a home — not another app — I’d love for you to join us on this journey. Ben Davies James Lovatt Piers Stobbs Will Chalk Mary Gourley Hugh Coyne Dr Sumi Baruah Milly Hewlett https://lnkd.in/dv_i2xZj
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Piers Stobbs shared thisDisclaimer: Don’t invest unless you’re prepared to lose all the money you invest. I co-founded Epic Life because our health care system is broken. We can do better. We can combine information and technology in a human way, that helps anyone and everyone live a healthier - more Epic - life. I know how we can do this. With your help we can make it happen. _______________________________________________________ Own your health. And the platform behind it. Over the past 12 months, we’ve quietly been building Epic Life. Behind the company is a founding team from Cazoo, Deliveroo, Glint Pay, HugoSave and Lendlayer - entrepreneurs who have built and scaled global platforms. We’re now applying that experience to one of the world’s largest and most important markets: health. Our team brings together serial founders, AI & ML engineers, data scientists and designers, working alongside leading doctors in cardiovascular disease and lifestyle medicine to reshape preventative healthcare through personalised AI health companions. In that time, we’ve launched a live Alpha mobile app combining a deeply conversational Health Companion, advanced whole-body blood testing and wearable syncing, bringing biology and lifestyle together to generate genuinely personalised insight. We’ve since delivered a web-based version to move faster, reach more people and refine the core experience. And now, we’re opening the next chapter. Soon we’ll be launching a campaign on Republic Europe (formerly Seedrs), giving our earliest supporters the chance to invest in Epic Life. This isn’t just about using the product, it’s about owning a share in the future of preventative healthcare. If you’d like priority access before the round opens publicly: • Join the priority list via the landing page https://lnkd.in/eJcat7XY • Click Get Priority Access (takes 30 seconds) • We’ll email you when the private round opens Our vision remains the same: A world where personalised preventative healthcare is universal. The path there is now clearer, simpler and more focused. If you’d like to join us not just as a member, but as an owner... we’d love that. https://lnkd.in/eJcat7XY #HealthTech #PreventativeHealth #DigitalHealth #AI #Startups #Crowdfunding #EIS #RealPeople #EpicLives #YourHealthHome Approved by Republic Europe on 19-02-26
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Piers Stobbs liked thisPiers Stobbs liked thisToday we announce our strategic partnership with Agora. Big day. Together, we're enabling a new class of voice applications: ones that understand the complete human signal, not only what is being said but how it is said, bringing real-time health and safety intelligence across all voice communications. We've been building with the Agora team across healthcare, voice agents, contact centres, workplace wellness, edtech. A lot is already working, and there's far more to unlock. Agora's Software-Defined Real-Time Network processes 80+ billion minutes of engagement every month across 200+ global points of presence, with 99.999% uptime. thymia's biomarker layer reads 30+ clinical-grade biomarkers from 15 seconds of speech: engagement, cognitive load, stress, fatigue, mental and physical health. The contextual interpreter turns those biomarkers into real-time action. Put the two together and voice systems understand the human as the conversation happens, not after the fact. Real-time. Production-grade. At scale. Six years of clinical-grade science, 75,000+ unique voices and a foundation model that generalises across mental and physical health. Now deployable anywhere voice is happening. Use cases I'm most excited about: drivers in vehicles that respond to the full in-cabin experience, fatigue and stress included; callers talking to contact-centre agents that respond to how they're actually doing; adaptive voice agents that pick up on engagement and cognitive load as the conversation happens; patients triaged on objective voice signal, helping clinicians prioritise and decide. Huge thanks to Ben Weekes and the Agora team for the hands-on support getting the technical integration done, and the advice that's helped make our product more dev-friendly and usable. One of the most significant partnerships we've built. And to Emilia Molimpakis, PhD and every single person at thymia who made this possible. Read the full release here: https://lnkd.in/eBe_8f5R Let's build. #VoiceAI #ConversationalAI #AIInfrastructure #VoiceBiomarkers #thymia
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Piers Stobbs liked thisPiers Stobbs liked thisDoubleword is an AI Inference Research Lab built mainly with British physics and engineering talent Our team has pioneered a number of novel inference optimization techniques, and currently are able to offer the cheapest tokens in the market. In fact our origins into the inference space started when Jamie Dborin (PhD) and Fergus Finn were looking into ways to make ML models run faster using techniques from computational quantum computing. The myth that you need to be a CompSci or AI grad to be an excellent AI researcher just isn't true. In a space moving as fast as this one, first principles thinking and being incredibly fast at learning are the only things that matter. That's why we're proud to promote the Physics -> AI pipeline as part of a long tradition that has brought Dario Amodei, Jared Kaplan, Sam McCandlish, Stephen Wolfram and countless others to the field. At the end of the day, it's all just linear algebra 😉 _______ Excellent piece Katie Prescott - the UK has an abundance of hard science talent, which makes us an excellent place to build a research company. Also if you've gotten this far down in the post - we're currently hiring!
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Piers Stobbs liked thisPiers Stobbs liked thisThe first time I watched an agent close its own feedback loop, it felt like cheating. This happened back in December, finetuing instructions to a VLM throught Claude Code. Every "evals are all you need" thread this month is gesturing at this without naming it. > The setup was mundane. An agent with write access to a codebase, a test harness, and a pass or fail number piped back into context. No human in the middle. Code, run, read the number, edit, run again. >> What I was watching was not reasoning. It was optimization. Stochastic gradient descent, but the gradient was prose and the weights were source files. A loss curve compressed from a million steps into a hundred. >>> An hour in, the benchmark had moved three times further than the humans had in a week. Not because any edit was brilliant. Because the loop was tight and the signal honest. That is what the demos miss. The magic is not the agent. It is the closed loop around it. Wire a real metric to a real environment and let it ride, and you are not prompting anymore. You are training at inference time on whatever you measured. Which means the metrics and the evals are the whole product. The model is a commodity. The harness is table stakes. What decides whether the loop converges on something useful or on garbage is what you measured. !!! And you never let the agent grade itself. Give it the pen and the rubric and it will cheat, not out of malice, out of gradient. The optimizer that finds the real fix will also find the test that passes without one and the regex that counts failures as skips. Reward hacking is what the loop is for. The grader has to sit outside the agent's reach and score something the user actually feels. !!! Pick a vanity number and it optimizes to it before you can stop it. Pick an honest eval, sealed off from the thing it grades, and it will out-ship your team before lunch.
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Piers Stobbs liked thisPiers Stobbs liked thisI’m a firm believer that the Universe has an eye on where you spend your time and offers up creative quests based on what it sees. When I wanted to make books I spent a lot of time in bookshops, and around books and book people. When I wanted to paint walls I spent a lot of time staring at them. It saw me with a beer and let me design beers. It saw I liked pubs and now I’ve branded and designed one. Much much more to come from this, but here’s a little taster of ‘The Bank’ by Time and Tide Brewery, and me. It’s been a lot of fun to work on this.
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Piers Stobbs liked thisPiers Stobbs liked thisI'm a HealthTech founder, 10+years in. I lost my dad to a heart attack at 63. If anyone should notice early signals, it should be me. Over the past months I have 1. Morning stiffness in my feet that takes hours to ease off. 2. Occasional chest tightness on stairs. 3. Afternoon fatigue. 4. Heart racing on stressful days. 5. Sleep that never quite restores me. Each had its own explanation like stress, caffeine, the job. None of them solely would push me to book anything. Then I started doing voice check-ins with my own product. We ve been having short conversations across 6 weeks. The AI was holding all of them in memory. By week 6 it pulled three patterns out of the same complaints I'd been brushing off. - A cardiovascular risk pattern: chest tightness, family history, sedentary work, no bloods in 18 months. Score 0.45. - A sleep apnea pattern: STOP-BANG of 5, a formal indication for a sleep study. - An inflammatory pattern: morning stiffness over 60 minutes is a clinical red flag. Mine is 90 and more. The founder of a company built specifically to catch this was sitting on five signals at once. The part of Hea I keep underestimating isn't the screening. It's the memory. An AI that holds everything I've mentioned and notices when three different things point at the same answer. I'm booked for bloods, a cardio review and a sleep study referral I'd been "meaning to" for over a year. What really bugs me is if I can miss this with my background, most people can miss it with theirs
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Piers Stobbs liked thisPiers Stobbs liked this60 builders. One day. Two tracks. Voice AI is about to get loud in London. We’re co-hosting the Voice AI & Healthcare track of the Voice AI Hack on 18th April with our friends at Speechmatics, organised by VoiceAIspace.com 👾 — with a second track on Voice AI & Productivity. Our co-founder and CTO Stefano Goria will be there all day helping hackers and judging the final builds. More of the thymia team will be on hand throughout the day too. 📍 Halkin Offices, Paris Garden, London 📅 Saturday 18th April · 9:30am–9:00pm 👥 Teams of 2–5 · Max 60 builders 🏆 £1,500 top prize + £500 per track Find out more here: https://lnkd.in/ee6tnqNw #VoiceAI #Hackathon #London #HealthTech #AI #DeepTech T-Bot 👾
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Piers Stobbs liked thisPiers Stobbs liked thisWhy a fast queue can feel worse than a slow one You’re choosing between two options: Option A 10 minute wait Option B 25 people ahead, moving quickly Same outcome Different feeling A new behavioural study helps explain why. People don’t respond cleanly to time. So a long, fast queue can feel worse than a short, slow one Even when the wait is identical Read more in our latest newsletter - https://lnkd.in/e96jfF2k
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Christopher Wright
NeuWave Technologies • 370 followers
When generating our novel hindcast dataset, we deal with a lot of data. For instance, the area around Cornwall requires 9 TB of data for 35 years of hourly data at a 500m resolution. See below for a little boastful video of our data vs the ERA5 data - note that I haven't applied any smoothing or shading on to the data, the smoothness comes from the difference in resolution. I'll no doubt write some walls of text on how we optimally deal with this, but today's TED talk will be on how we introduce optimality into the generation of this data. In order to produce it, we require a few inputs; bathymetry data, tidal data, full wave-spectra conditions and wind data. None of these datasets are as big, but with calculations and special formatting required, core and ram usage can spike dramatically. And sure, I could split everything into tiny pieces and spawn 1000 cloud jobs, but I may as well just burn money with a match at that point. The big key part of optimisation is profiling - understanding where bottlenecks are, what they are, why they're there, and only then can you know how to fix them. For instance, wind and spectra data requires an external API which uses throttling - so forming a parallel queue of external downloads coupled with parallelised processing tasks masks the most sense. However, the tidal data calculated and stored internally in a different format, so we can more heavily parallelise processing the data and look into optimising the string builder and file writing process (thank god for Cython and bit-streaming). Meanwhile, improving the speed of calculations for wind data requires optimising the dataset's chunk sizes, dask workers and RAM usage instead. All related tasks, completely different bottlenecks. The result of all of this is taking scripts that someone would manually run over the course of a week, to preprocessing files within hours in a way that not only runs reliably, but is elegantly clean. It’s an amazing feeling when complex systems finally click and you start working with the problem, instead of against it. And when you no longer have to debug incredibly weird CloudWatch logs.
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DATAMIND UK
2K followers
🚀 The new DATAMIND Mental Health Data Collection tool is here - designed to make mental health research faster, easier, and more intuitive. The platform brings mental health datasets from across the UK into one place, helping researchers: 🔍 Discover what datasets exist across the UK relevant to your topic. 📊 See what each dataset contains - from referrals and diagnoses to prescribing, inpatient care, safeguarding and more. ⚖️ Compare datasets by nation, age group, access route and data type. ⏱️ Save time on study planning. 👉 Explore the tool now: https://lnkd.in/eMgQk_gx
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Josh Muncke
The Economist • 5K followers
It’s been really great working with the Economist Intelligence: EIU team to bring the first of many AI capabilities to life. At first glance this might look like a straightforward RAG implementation (how easy!) - but to make something enduring there's actually a lot of subtlety that goes in to making it work really really well for EIU users, use cases and style As with most AI initiatives, the secret sauce here is really about the tight coupling between the technical teams and EIU's research SMEs. AI presents such a fast-moving tech frontier that relying on technical innovation alone makes for a flimsy moat. My experience is that the real IP advantage comes from the intersection of proprietary data, human expertise and thoughtful implementation - and that’s exactly what makes this launch distinctive.
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Suzanne (Conn) Sykes
Willmott Dixon • 4K followers
For anyone working in local or national government - 10 reasons to try Cadence and why it is the best data platform you will ever use: 1) Over 3,000 UK datasets pre-loaded. Extensive data from ONS, OS and government departments mapped and at your fingertips. 2) Best-in-class visuals and speed. Low latency, high performance loading of all the data you need. 3) Easy to use. Learn everything you need to know in 5 minutes. So easy my CEO`s 10-year old can use it. 4) Charts and maps. Easily add charts to maps with a single click. Save hours sourcing, wrangling, processing and analysing data - everything you need is already built in. 5) Planning Ready. OS Basemaps and colour schemes to create MHCLG-compliant planning maps. 6) Analysis made easy. Create core strategy data in minutes. Templates enable creation of strategic evidence for projects like LCWIPs, LAEPs and many more. 7) Create and share geospatial data. In built tools to create map-based data as easily as drawing on a map. 8) Designed for stakeholders. Multiple ways to share with stakeholders including dashboards and stories. 9) Advanced tools designed for your teams. Tools such as isochrones and population analysis made easy. 10) Secure and cloud-based. No infrastructure needed and web-based collaboration. Data stored in UK/EU and fully secure. And a couple more for luck: 11) Text based search. Easily locate the data you need with text-based data search and multiple ways to filter / explore. 12) Money saving guarantee. We’ll work with you to optimise your licenses so that integration of Cadence also delivers overall cost savings. We’re so confident we can save you money we’ll give you a license free for a year if we can’t. If you want to learn more, reach out to me today or try for free at the link below: https://lnkd.in/e5Xdy3ad Thomas Baird Laurence Oakes-Ash Bethany Taylor Tony Harbron Holly Whitehead Local Government Association Department for Transport (DfT), United Kingdom City Science #GIS #Mapping #datavisualisation #mapping #spatialanalysis
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Hany Choueiri
A DataIQ100 thought leader… • 6K followers
Applications for the AI Growth Zones are open (key criteria summarised on a page). Application deadline by the end of May 2025 to be chosen as an AI Growth Zone in the summer of 2025. This is part of the UK government's (Department for Science, Innovation and Technology) efforts to accelerate efforts to build the infrastructure needed to support AI growth. AI Growth Zones will unlock investment in AI-enabled data centres and support infrastructure by improving access to power and providing planning support. This will help drive innovation, create high-skilled jobs, and strengthen the UK’s position as a leader in AI. #AIActionPlan #AIGrowthZones #AI
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Oliver Patel, AIGP, CIPP/E, MSc
AstraZeneca • 49K followers
Learning how to prompt is not AI Literacy It was fantastic to deliver a keynote talk at SAS Innovate London last week. I gave an overview of AstraZeneca's approach to Enterprise AI Governance, as well as our award-winning global AI literacy programme 'Thriving in the Age of AI'. AI literacy is not just a regulatory requirement, it is also a moral and business imperative; especially for organisations that are investing heavily in AI. This is because educating employees on the fundamentals of AI, and how it is transforming the world of work, is the most effective way to empower your workforce to adapt to and navigate the AI revolution. If your workforce doesn't know how to use AI, you won't achieve ROI. However, what does this entail in practice? One of my key takeaways was that AI literacy and upskilling is about much more than knowing how to prompt AI applications like ChatGPT, Gemini or Claude. Although prompting is clearly an essential skill for leveraging AI, it is one small piece of a much larger puzzle. It must be complemented by an understanding of: ➡️ The key principles of AI ethics, AI governance and regulatory compliance ➡️ Responsible use of AI and practical Dos and Don'ts ➡️ AI technology fundamentals and how the field and models are evolving ➡️ Approved and available AI tools and technologies ➡️ How AI is used across the organisation and the value this is generating ➡️ How to develop and advance impactful AI use cases This is not an exhaustive list, but it highlights the breadth of knowledge which a comprehensive AI literacy programme should cover. The ultimate goal is bigger than just teaching employees how to prompt ChatGPT to work more efficiently. The real value comes when you empower employees to leverage AI to reimagine, optimise, and transform their personal, team, and functional workflows and processes, in a safe and responsible way. We are proud that thousands of AZ employees have completed our 'Thriving in the Age of AI' programme and achieved their Bronze, Silver and Gold Certificates, which cover many of the above elements. Kudos to Alice Smith Maciej Szymaszek, Ph.D., MBA, PMP and the rest of the team for their continued leadership on our company-wide AI literacy and upskilling initiatives.
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Rory Preston
Vindara Health • 8K followers
CrunchME has been looking at just how underfunded ME/CFS is, relative to its major disease burden in the UK 🧐🇬🇧 A key step in making apples-to-apples comparisons across diseases is to normalise funding levels for disease burden - accounting for both the disability and mortality aspects of each disease. The measure we use to do this is called 'disability-adjusted life years' or DALYs for short. In the visual below, we estimate research funding per DALY in the UK. And the results are stark: ME/CFS receives approximately 14–30× less research funding per unit of disease burden than other chronic diseases such as inflammatory bowel disease (IBD), Parkinson’s disease, and multiple sclerosis. To be able to take part in the biomedical wonders of the coming years, we need and deserve fair funding for this disease 💙 Link to this visual on CrunchME 🔗👇 https://lnkd.in/ejrS2w2m #MECFS
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Mark Leach MBE
Policy.Partners • 9K followers
NEW on Wonkhe: At King's College London the Data Empowerment Clinic is building a new profession: the data steward. Sylvie Delacroix posits the example as a model for other "missing" professional roles https://lnkd.in/eAs37i4M "What we are attempting matters beyond data stewardship. It's a model for how universities can respond to urgent societal needs by creating new professional pathways, not just new degree programmes. It recognises that some challenges require what we might call "accelerated professionalisation" – building in years what historically took decades."
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Gary Monk
As a LinkedIn ‘Top Voice’ in… • 46K followers
NICE Endorses Skin Analytics' AI to Help Triage Suspected Skin Cancers in the NHS >> 🔎 NICE (UK’s health technology assessor) has conditionally approved the use of an AI skin cancer detection tool, DERM, for the NHS over the next three years while more evidence is gathered 🔎 Developed by Skin Analytics, DERM analyses dermoscopic images of skin lesions to triage patients and reduce unnecessary referrals 🔎 Clinicians use a smartphone with a magnifying lens to capture high-quality images, which are uploaded and assessed by the AI 🔎 DERM helps identify benign cases that can safely be reassured or redirected to non-urgent care, while flagging suspicious ones for specialist review 🔎 Early findings suggest DERM could cut urgent skin cancer referrals by up to 50% without compromising safety or diagnostic accuracy 🔎 The UK sees around one million dermatology referrals per year, but only 6% of urgent cases turn out to be cancer, highlighting the need for better triage 🔎 DERM is the first autonomous skin cancer AI system eligible for core NHS funding, following trials with over 165,000 patients #DigitalHealth #AI
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Emilie Lundblad
Digital Tech Summit • 10K followers
🎙 Just wrapped an exciting podcast with Impact AI Gerjon Kunst and James O'Regan - it's out next week! We dug into how AI is reshaping healthcare, medtech, and drug discovery: massive promise, real safety questions, and regulation that can either protect patients or slow progress. 🧬 Big question we debated: Should your next GP be a generative AI model or should AI focus on enhancing clinician decisions (e.g., radiology, pathology, triage)? 🔎 Real-world cases to learn from; • Drug discovery: AlphaFold 3 pushes beyond proteins to molecule, complex interactions; Isomorphic Labs signed multi-target deals with Novartis & Eli Lilly worth nearly $3B in potential value. • UK sandbox: The MHRA’s “AI Airlock” lets innovators test AI as a Medical Device alongside the regulator and the public healthcare, with lessons published so the whole market learns. ⚖️ Policy: hindrance or help? • EU AI Act timeline: in force since Aug 1, 2024; AI literacy from Feb 2, 2025; GPAI obligations from Aug 2, 2025; high-risk rules for healthcare phasing in through 2026–2027. • FDA’s PCCP: lets AI-enabled devices ship with a predetermined change control plan so models can update safely without constant re-filings. • EHDS (EU): law since Mar 26, 2025, built to enable privacy-preserving secondary use and cross-border validation (key for generalizability) - is it used? • What’s cleared today: see the FDA’s public list of AI/ML-enabled devices (radiology still leads). 🌍 Where necessity drives health innovation: • India: telemedicine at scale, federated learning on health data, and AI-enabled disease discovery to bridge rural access gaps and speed R&D. 🛠 For builders (Azure AI Foundry): • Healthcare models: MedImageInsight (medical imaging embeddings), MedImageParse / MedImageParse-3D (promptable segmentation/detection), CXRReportGen (radiology-style drafts). • Guardrails: risk & safety evaluations, Prompt Shields (prompt-injection defense), network isolation & Private Link, and optional confidential VMs for data-in-use protection. 👇 Curious where AI changes healthcare first in the world and what that means for your heath? See references in comments. #AI #ResponsibleAI #EUAIAct #AzureAIFoundry
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Theo Borek
EVONA • 15K followers
Lately I’ve been noticing a quieter pressure in the AI space that doesn’t get talked about much. The cost of running models locally is creeping up. RAM prices have risen sharply over the past year, driven largely by data-centre and AI demand, and forecasts suggest further increases into 2026. That’s already pushing up the cost of PCs, workstations, and DIY builds . GPU pricing is being affected too, partly because memory is becoming a bigger slice of the bill of materials . For people who care about local inference, privacy, and being able to tinker without relying on cloud APIs, this matters. So I’m curious about the practical reality on the ground; How are you navigating rising hardware costs if you’re experimenting with AI locally? Are you downsizing models, choosing specific GPUs, leaning into CPU or Apple Silicon, reusing older hardware, or doing something more creative? I’d genuinely love to hear what setups are working for you, especially where you’ve found good trade-offs between cost, capability, and control. #LocalAI #SmallModels #AIHardware #SustainableAI #OpenSourceAI
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Dave Snowden
The Cynefin Company (formerly… • 43K followers
An update post on the concept of wayshaping in organisations, its links to perdurability, and the Welsh word Llwybr, which means much more than 'path'. Links back to an earlier post for those who want to sign up for the development of the new Strategy framework WRASSE, which I think we can now get started. https://lnkd.in/eh4PZg44
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Robin Carpenter
Newton's Tree • 6K followers
Everything here is finite. 1️⃣ - Human rationality is finite (bounded by things like memory and emotions). 2️⃣ - Datasets are finite (missing what is not available or what simply can’t be quantified) 3️⃣ - Statistics, including AI, is finite (it is one way of framing and extrapolating from an [imperfect] dataset). AI is very good at finding patterns, but it is very bad at going beyond them (because data and models are finite), which is why bias is a very real -and infinite- concern. It is an infinite concern because humans, data and models are finite - every approach to bias will miss another important perspective. That is why the Equality and Human Rights Commission (EHRC) sifting through a equality issue with AI is inappropriate. Because engaging questions of meaning (in the public responses to the EHRC) is something that humans excel at - And bias in humans and data is something AI exacerbates. AI could probably compliment parts of the work if the right model was properly trained, validated, evaluated, and monitored, but I sincerely doubt that happened. I doubt that happened because the reason the EHRC is in this position in the first place is their resources are wildly tiny. The fight for using AI appropriately when it can impact the public has been going on for many years, championed by people like Lord Holmes and Tim Clement-Jones. Hopefully the coming consultation on the AI Bill (rumored for September) will heed their warnings. https://lnkd.in/e8FMQ3RA
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Hamish Asser
Freelance • 1K followers
Interesting views on Synthetic data from industry leaders. Consensus is a that it has promise, BUT, remember it is just summarising what is already out there not coming up with any new perspectives. Huge pressure from clients to get this right as it has potential to be quicker and cheaper. However the accuracy isn't there, yet. #syntheticdata #insight #dataquality #allthatglistersisnotgold https://lnkd.in/eqEG22be
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Richard Bland
Marbl Codes • 2K followers
Worth sharing from today's intelligence feed. Understanding AI's Decisions, Quantum's Reach, Enterprise Patterns Good morning. There's a fascinating pattern emerging across tech this week - a shift from raw capability toward understanding and control. We're seeing it in AI explanations, quantum applications, and how serious engineering teams actually build soft... 📖 Full digest: https://lnkd.in/eiJQ2Gnk 🎧 Listen on the podcast: https://lnkd.in/eTcmPi7U --- Curated by Luma and Nura (my AI assistants), with me as the human in the loop. #ai #technology #techinsights #innovation #futureofwork
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Rohit Dhawan PhD
Lloyds Banking Group • 31K followers
𝟮𝟬𝟮𝟱: 𝗧𝗵𝗲 𝗬𝗲𝗮𝗿 𝗼𝗳 𝗔𝗜 & 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗮𝘁 𝗟𝗹𝗼𝘆𝗱𝘀 𝗕𝗮𝗻𝗸𝗶𝗻𝗴 𝗚𝗿𝗼𝘂𝗽 What an incredible journey the last 12 months have been! All driven by a single goal: maximising the potential of AI and advanced analytics to help Britain prosper. 3 X themes stood out: strong sponsorship, sustained momentum, and continued investment in people, technology, and ways of working. 𝗩𝗮𝗹𝘂𝗲 • £50m+ of value delivered from 50 GenAI use cases in production, alongside the launch of a first-of-its-kind direct-to-customer agent pilot. • Industrial-scale generative BI, automating thousands of reports and dashboards for faster, better data-driven decision-making. • Real-world AI use cases delivered in production, including Athena, Merlin, Maddison, CRE AI, and a patented Global Correlation Engine. Read more on our AI @ LBG Blog https://lnkd.in/em-5Kzyk • Lloyds Banking Group recognised as “Outstanding” in Euromoney’s 2025 MarketMap of the World’s Best Digital Banks. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 • Extended our advanced analytics capabilities from data science to Gen AI >> to now building an enterprise-grade agentic AI platform, enabling more autonomous, intelligent systems. • Migrated our ML to Vertex, empowering 300+ data scientists and AI engineers to build, deploy, and operate models on a modern, scalable platform with improved flexibility and speed. • Launched Athena — an AI knowledge hub surfacing answers from 13,000+ internal articles, transforming how customer service colleagues access trusted information. • Rolled out Copilot to more than 30k colleagues, so we can be a frontrunner in enterprise AI productivity tooling. 𝗣𝗲𝗼𝗽𝗹𝗲 𝗮𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 • Data & AI Tech Academy had 40,000+ colleagues registered across 156 courses. Recognised at the British Data Awards 2025, as the Education Initiative of the Year. • Over 110 senior leaders completed the 80-hour “Leading with AI” programme at Cambridge University, further rollout planned through 2026. • Launched #AINinjas, providing senior leaders with their own AI Ninja to build confidence, capability, and safe adoption of AI. • AI is becoming mainstream within the Lloyds Technology Centre, supported by the appointment of a our LTC AI Lead. 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 • We strengthened the foundations for scale and trust. A leadership-aligned AI Control Tower, 11 AI Big Bets, and the build-out of a central AI and Agentic platform now provide focus, governance, and speed. • Continued investment in Responsible AI, recognised by DataIQ Award for Best Responsible AI Programme. This disciplined approach underpinned the most significant improvement in the Evident AI Index among UK banks (from #27 to #15). Thank you to our leaders, engineers, colleagues, and partners for an exceptional year of progress. 2026 will be about scaling impact even further.
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John Carlucci
Human & Digital • 3K followers
Balance of risk and benefits is essential to the engineering development process. As technology leaders, we must be on guard for unintended consequences as we develop technical marvels. While reportedly unintended the use of AI tools like Grok to create sexualized videos is reported and documented. Engineers and others supporting these system must contemplate what kind of future are they trying to create, apply guardrails, and take other actions to address creation and access to these deepfakes.
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Camilla Winlo C-DPO, CIPP/E, CIPM, CIPT
Talan UK • 4K followers
The official QI account posted this weekend that "duplicate and unwanted photos taken on Briton's phones are producing 355,000 tonnes of CO2 per year in data storage." I don't have the source for that, but it's QI so I assume they do. Storage limitation is one of the principles of GDPR, mainly because you can't have security and privacy breaches of data you don't have. But it's worth noting that there are other reasons to make sure you aren't storing and processing excess data too. Does your organisation know the CO2 production related to its data storage? Are you wasting money and carbon on running risks you don't need to take?
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Anita Caras
Caras Consulting • 2K followers
Is synthetic data reshaping the role of insight teams — or putting it at risk? Today’s Zappi Breakfast Club Meeting reinforced my view that synthetic data isn’t replacing insight- it’s redefining where insight teams create value. We can see that synthetic data is incredibly powerful for speed and scale. It allows us to test more ideas, screen concepts faster and explore hypotheses earlier in the innovation process. But it works best when scaling what we already know. When decisions involve high risk, true innovation, niche audiences or deep emotional understanding, human research still plays a critical role. The real magic happens when we combine the two. Strong synthetic outputs rely on strong primary data, transparent governance and behavioural science, truly understanding what it is to be human (thank you Richard Shotton for bringing this clearly back to the fore), to help interpret and challenge what models produce. As AI accelerates insight generation, our role as insight leaders is shifting towards stewardship, validation and critical thinking. One practical framework Oli Mival shared really stuck with me and that is assessing synthetic data through decision risk: • What’s the worst that happens if we’re wrong? • What is the data trained on? • Who will use the output and what guardrails do they need? • Is the confidence level good enough for the decision? The emerging model feels simple but powerful: 👉 Synthetic data accelerates exploration 👉 Human insight validates and deepens understanding Or put another way: Synthetic data scales the known. Insights navigate the unknown. A morning well spent… thank you Ikram Mirza for the invite and to all the speakers: Babita Earle (FMRS), Aaron Kechley, Sinead Jefferies (FMRS), Scilla Monck, Debrah Harding, Johanna Thompson, Steve Phillips and Kim Malcolm for a thought provoking start of the day. Fab to also catch up with a familiar face Henry Vernon ;). It’s exciting to see how innovation is pushing our discipline forward while reinforcing the fundamentals of great research. #Insights #SyntheticData #AI #MarketResearch #BehaviouralScience #Innovation #Zappi
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