Paul Butcher

UK FPTP (first past the post) electoral system vulnerabilities. Electoral Calculus is a well-regarded polling / MRP outfit in the UK. The image is their latest prediction of the most likely outcomes of the upcoming GE. It has the Tories on 23% of the vote, with a central prediction of 66 seats out of 650 (so about 10%) but with a massive range of uncertainty - anywhere between 37 and 225 of the seats. The fact that it's potentially so volatile, in terms of seat outcome, is apparently based on uncertainty as to the precise impact of Reform UK (Farage)'s 12% on sapping the Conservative vote. While in some ways I wouldn't exactly weep at a Conservative wipeout, the fact that the difference in seat outcome is *so much* more volatile than the likely overall % changes does seem to illustrate the vulnerability of FPTP as a voting system. Whichever party it is, I don't think one party winning 519 seats out of 650 on around half of the vote is a good outcome in a Parliamentary system, especially not the 'winner takes all' version which we have in the UK. This sort of system weaknesshas long been ignored when the two main parties still have representation in the 100s of seats, as it's only affected the 'lesser' parties and the two big ones seem to long for complete power without the tedium of coalition. I wrote a piece a while back noting that we've seen in microcosm already where things could end up, in the form of 2015 general election in Scotland, in which the SNP won over 90% (56 out of 59) Scottish seats in the House of Commons on just under 50% of the vote. Fortunately the existence of the Scottish Parliament and its proportional representation system kept the other parties alive and able to recover. But there won't be that safeguard in this case. And yes, of course the big parties are themselves coalitions in a certain sense, but privateish debates within Labour or Conservative factions are no substitute for public debates fronted by different parties, whatever one may think of the quality sometimes. Links: EC's main table - https://lnkd.in/etWPkX_T EC's April 2024 voter migration analysis - https://lnkd.in/ey44AZRX EC's June 2024 commentary (before today's announcement by Farage) - https://lnkd.in/eUaydqD6 2015 UK GE in Scotland - https://lnkd.in/eAUTzr27

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Tomorrow I’ll be hosting the first of a series of webinars to explain why the Flexible AI Upskilling Fund is for you 🫵 If you are a professional, based in the UK working for an SME, you may be eligible for up to £10k in grant funding to train your people in AI. In this webinar I'll cover: • What AI could do for your business • What is UK government's 'Flexible AI Upskilling Fund' • Eligibility and funding details • The application process & how to apply • How to select the right AI training I'll also be releasing exclusive content, to help you make a successful application. If you don’t think AI is for you, think again. You don’t need to be able to BUILD AI systems to USE AI systems. AI is for everybody and I’ll show you why. Register for the webinar here: https://lnkd.in/egTtwDuT

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➡️ AI4C (AI for Charities) Community … Thanks and recognition for content to David Gewirtz at ZDNET “Unless you've been hiding on a deserted island somewhere without any internet service, you probably know that OpenAI released its new large language model, GPT-4o, where "o" stands for "omni." The new LLM is supposed to offer a variety of modes, including text, graphics, and voice. In this article, I'm subjecting the new GPT-4o model to my standard set of coding tests. I've run these tests against a wide range of AIs with a wide range of results. You'll want to read all the way to the end because I did get a surprising result. If you want to follow along with your own tests, point your browser to this article: How I test an AI chatbot's coding ability - and you can too. It contains all the standard tests I apply, along with explanations of how they work, and what to look for in the results. And, with that, let's dig into the results of each test and see how they compare to previous tests using Microsoft Copilot, Meta AI, Meta Code Llama, Google Gemini Advanced, and ChatGPT. Here are the overall results of the five tests: ChatGPT GPT-4o: 4 out of 4 succeeded, but there's that one weird dual-choice answer Microsoft Copilot: 0 out of 4 succeeded Meta AI: 1 out of 4 succeeded Meta Code Llama: 1 out of 4 succeeded Google Gemini Advanced: 1 out of 4 succeeded ChatGPT 4: 4 out of 4 succeeded ChatGPT 3.5: 3 out of 4 succeeded Up until now, my default go-to for programming help has been ChatGPT. It's just worked (except for when it didn't). All of the other AIs failed most of my coding tests. But GPT-4o is weird. That last answer kind of raised the hairs on the back of my neck. I'm not thrilled with getting two answers for one question, especially when one answer contains code that the language itself doesn't support. What's going on inside GPT-4o that's causing this loss of confidence? In any case, it's still the best-performing AI for my coding tests, so I'll probably continue to use it and get more acquainted with GPT-4o. Another option is to go back to GPT-3.5 or GPT-4 in ChatGPT Plus. Stay tuned. The next time ChatGPT updates its model, I'm definitely going to rerun these tests and see if it's smart enough to pick the right answer for all four tests. Have you tried coding with Copilot, Meta AI, Gemini, or ChatGPT? What has your experience been?” https://lnkd.in/eXHKHtJ4

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This is another useful proof point of the need for #AI re-skilling across all companies and organisations. Siobhan's list of her own re-skilling and educational activities is a tribute to her inquisitive mind and resilience. It's clear that there's some great material out there from the big tech players and leading universities. What is less clear is what you need to do - at a personal or organisational level - to re-skill and reposition yourself. There's simply so much out there. With this in mind, my co-founder Shivika Pratap and I are completely reshaping https://HeyDeesha.ai to focus on guiding careers in the context of the AI economy. We are doing our reshaping based on a taxonomy of roles that we see emerging. Please DM me if you are interested in what the taxonomy looks like. It's not just tech roles, BTW. We want to extend the taxonomy to Marketing, Sales, Support... and, one day, really deep specialist skills such as Medicine. We are also looking at how the pace of change in the workplace is affecting maternity leavers/returners. Kate Apaflo Awuku-Darko, Emmanuel Ihenacho

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🔔 Funding Alert for UK SMEs 🔔 The Department for Science, Innovation and Technology (DSIT) launched a £7.4m pilot scheme yesterday to subsidise the costs of AI training for SMEs in the UK. Eligible businesses are able to apply for for funds to cover up to 50% of their AI training costs. To be eligible, you must: - Be registered and operate in the UK - Employ between 1-249 employees in the UK - Have been operating for at least 1 year - Be able to match-fund 50% of the cost of the training You can get between £2,500 and £10,000 in grants, depending on your business size. You'll be responsible for finding your own AI training provider (*massive, dramatic cough and lots of pointing at myself*). Applications are now open, but it's a short pilot window - they'll close on 31 May. To apply, head over here: https://lnkd.in/e6PGNqZg It's a big step in the right direction - very best of luck to all who apply. PS Need some help with the AI skills bit in your application? I've opened up some totally free 1:1 slots for this very purpose: https://lnkd.in/eD2HeUb3

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#MACH3 - Some Reflections I've not given an update on MACH 3 yet, partly because it's always good to take some time to ponder but also because I caught Covid in New York and have felt wretched since getting back! As always, MACH 3 was a great opportunity to immerse myself in an environment where there are a lot of smart people doing a lot of smart things across a number of industries. The number of invaluable conversations snatched in queues for lunch and outside the venue soaking up the NYC sun (for us Brits this is a real novelty) almost out-weighed the more formal presentations. For me, this was a "MACH in Transition" conference, where MACH 2 was all about the energy and enthusiasm of something new and exciting which has starting to bear fruit, MACH 3 was more about "OK we've adopted the MACH principles, now what?". There were definitely one or two stand-out presentations ( Justin Thomas, take a bow ) and by the end of the conference there was definitely a sense of deja vu once the final customer had detailed their transition to a MACH-aligned, composable architecture. That's not necessarily a criticism, more an observation of actually how successful MACH has been in a very short time period. A broad spectrum of very different companies have all had demonstrable success implementing these principles, with a catalogue of MACH certified products now part of their estate, all delivered in the time that some organisations would define the requirements for their next big [insert monolith here] upgrade. The challenge now, and one for MACH 4 for me is about "how do we sustain this", and beyond the technology side of things, what are the processes, people, ways of working required to ensure that this becomes a long-lived part of the organisational fabric. From a personal perspective, for MACH to be truly transformative and sustainable within an organisation, it needs to be delivered with a Product-first mindset, with cross-functional Product teams set-up to deliver at pace and with autonomy. We don't talk enough about what makes MACH difficult, but one obvious by-product of the composable approach is clearly dependency management. If those dependencies aren't managed (and broken) then quickly your estate will become overly complex and start to impact pace of delivery. MACH architectures are complicated. You need really strong engineers to work in this environment, you need strong Product Owners that understand how to manage their Product end-to-end, and you need a completely different support model to manage these Products compared to the more traditional approaches. DevSecOps and Platform Engineering as disciplines need significant elevation within your business. It's hard, but as those who took the stage at MACH 3 will testify, it's worth it. MACH 4 needs to go deeper into some of these more transformative principles and what MACH means for your org design, and talent you need to recruit into your business. #MACHALLIANCE

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That's Q1 in the books, and what a chapter it's been. Here are some of my thoughts on the quarter: Bucking the trend in a world bracing for moderation, European tech funding surged to a commanding €32 billion, up 20% from last year. This isn't just growth; it's a bold statement of confidence from investors who see the old continent as a cradle of innovation. And the startups? They're not just surviving—they're pioneering. Particularly in sustainability, where new ventures are snapping up 35% of investment capital, signaling a green revolution in the entrepreneurial world. Amid this financial fervor, the talent pool is deepening, with tech hubs from Berlin to Barcelona brimming with savvy coders and visionary creators. Diversity is becoming more than a checkbox—it's a competitive edge, as 25% more startups are boasting multicultural founding teams compared to the year prior. These days, if your toaster isn’t AI-powered, is it even toasting? Everywhere you look, it's AI this, AI that. I half expect my morning coffee to predict my day. #AI's the new black, the secret sauce, the—dare I say—kale of the tech world. Seems like you can slap an 'AI-powered' label on anything these days and watch it fly off the shelves. Toothbrush? AI-powered. Refrigerator? AI-powered. Your pet rock? Now with AI! But jokes aside, amidst the AI fanfare, there's some genuinely groundbreaking work being done by the likes of Google DeepMind, Anthropic, Mistral AI and OpenAI, and we've seen over 500 AI-driven startups pop up, ready to teach our machines some new tricks and maybe even some old ones (yes, AI can now make a mean cup of coffee). Then there was START Summit—envision it as the Cannes Film Festival for startups, minus the glitz but packed with far more innovation. Think of it as the Davos for disruptors, minus the political agenda, but bursting with startup energy. I'm super grateful that I got to be part of the organizing team for a third year running and had the chance to witness firsthand the magic that happens when Europe's brightest minds converge under one roof. The energy was electric, the ideas transformative, and the potential limitless. Our event confirmed that the bold, inventive energy often seen in Silicon Valley is alive and well in St. Gallen and the European Continent, signaling a bright future for the European tech ecosystem. The interactions and connections made at the Summit have already begun to bear fruit, sparking collaborations that I believe will define the tech landscape in the coming years. It’s clear that the spirit of innovation knows no boundaries and the sparks ignited here will light up industries and markets across Europe and beyond. So in a nutshell: we’re not just ready for Q2—we're rearing to go. Here’s to turning those 'I’ll e-mail you' into 'Let’s make something happen!' #Q1Review #EuropeanTech #StartupFunding #TechTrends2024 #EuropeanStartups #TechHubEurope #EntrepreneurialSpirit #FromTalkToAction #START24

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Hyperoptimisation from a product that works perfectly well seems to be incredibly value destructive for all concerned. Not sure why it happens so much in tech I learned today that something coming up imminently on our engineering road map is updating all our lambdas to be compatible with new AWS standards. Apparently this is something that will happen every 18 months or so forever and GCP is apparently even worse. If we don’t do this by the time AWS deprecates this functionality Spot Ship will stop working. However doing it will lead to zero improvement in functionality for us. AWS has literally spent money on engineering that has had no effect but to waste our engineers time and subsequently p*ss me off. They are not alone. There comes a time in a product life cycle where it feels engineering dollars are being spent for the sake of it. Why not either downsize workforce, or give the guys and girls a very long very well paid holiday (if trying to keep them out of competitor hands)??? While our product has got so much better over the last year (primarily by ticking off the most crucial of existing paying customer asks), I want to stay aware that at some point it will be essentially “done”. Any further “improvement” will just annoy clients. Engineers love to say SAAS is alive and never “done”…but I think this may be largely talking their book I’ve seen it a lot in consumer (e.g. having to update the Uber app when you just want to get a car back from the pub once every two weeks…despite them having added no noticeable new functionality for 10 years). This is the first time I’ve noticed it so clearly in B2B. #shipsandshipping #maritime #founder #vc

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This is the (anti-)pattern and I see it in my own engineers at times (because it is human nature). A story about how UK Borders chose to in-house the successful post-Brexit border solution after 3 years because of budget pressure. It beggars belief to think that something vital can be done more cheaply in-house that a company does for a living with a massive amortized R&D base - meaning you pay some small fraction of the actually costs of development and operations. Yesterday I learned the origin of Platform One was an effort to avoid paying $19M/year in licenses to a platform-as-a-service company (and to avoid feeling locked-in). Now Platform One is ~150 FTEs (~$50-70M/year est cost fully loaded and now your are mentally and technically locked-in). It happens as much in the commercial world as the government world. But in the commercial world, your competitors will pounce upon your folly and strike (see Predix). That same feedback loop isn't present in Govt, and without it I think all Commercial companies would do exactly the same thing (human nature). We are re-deriving from first principles why the tech business model exists at all: massive R&D costs are amortized across a large number of customers to create affordability and scale. Gregor Hohpe's article, "Don't get locked up into avoiding lock-in", provides a more robust way to think about these decisions: https://lnkd.in/gmUe9fNr And it is important to remember that the goal of Open Source was never to avoid lock-in -- it was funded to commoditize someone's compliments. https://lnkd.in/gATfyZBc https://lnkd.in/gJAVxcT4

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Here's a link to a short video I've made showing how RAG can be used to improve ChatGPT/GPT-4o translation output: https://lnkd.in/ed5cHXX3.

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945 days of delay under the Conservatives. 9 days to a green light under Labour. Excuse the pun (it's a solar farm!) - but the difference is Night and Day. Congrats @energygovuk and Ed Miliband Delays and Indecision Under the Conservative Government: Extended Examination Period: Initial Application Date: 18 November 2021. Application Accepted: 16 December 2021 (28 days). Examination Start Date: 28 September 2022 (286 days from acceptance). Examination Closure Date: 28 March 2023 (181 days from start). ExA Report Delivered: 28 June 2023 (92 days from closure). Repeated Extensions to Statutory Deadline: First Statutory Deadline: 28 September 2023 (92 days from report). First Extension Deadline: 7 December 2023 (70 days from initial deadline). Second Extension Deadline: 7 March 2024 (90 days from first extension). Third Extension Deadline: 11 April 2024 (35 days from second extension). Fourth Extension Deadline: 20 June 2024 (70 days from third extension). Total Delays Under Conservative Government: 945 days from initial application to last extension. https://lnkd.in/esNHmFFp

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Gemini AI: Your Productivity Powerhouse in the UK In recent months I've been using Gemini AI from Google and its rapidly become one of my most essential tools. As a busy professional in the your day is filled with meetings, deadlines, and the constant need to stay ahead of the curve. What if you could reclaim hours of your time and streamline your workflow? Google's Gemini AI is here to revolutionise the way you work. Here are three ways Gemini AI can transform your working day: Effortless Analysis of Regulatory Documents: Tired of spending hours sifting through complex regulatory documents? Gemini AI can quickly analyse and summarise key points, saving you valuable time and ensuring compliance. Policy Creation Made Simple: Drafting new policies can be a daunting task. Gemini AI can help you generate clear, concise, and compliant policy drafts, allowing you to focus on strategic decision-making. Elevate Your Communications: Whether it's crafting compelling emails, preparing impactful presentations, or creating engaging social media content, Gemini AI can help you communicate effectively and efficiently. Gemini AI isn't just about saving time; it's about enhancing your productivity, enabling you to focus on high-level tasks, and ultimately, achieving better outcomes. Ready to experience the power of Gemini AI firsthand? Email Connect@c-learning.net or visit our website https://lnkd.in/e4yM3h9u to learn more. #GeminiAI #Productivity #Efficiency #Innovation #AI

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The end of this post is brilliant! Eddie Short paraphrases Satya Nadella here: 'AI will not replace companies and economies, but companies and economies that lead with AI, will replace those that do not!'

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Gerard Reid kindly pointed me to this fab data set - a quantitative/qualitative review of ENERGY...arguably THE most important part of how human existence at scale sustains on Planet Earth! I've only ever met Gerard in person once - at a MOVE gig in London a few years ago - but I'm a regular listener to the REDEFINING ENERGY Podcast he presents alongside Laurent Segalen.🎙️ Of the 4 key takeaways from The Energy Institute Mr Reid suggests in his LinkedIn post earlier today - this one caught my attention the most! 'Fossil fuel demand is close to peaking: Demand in North America and Europe has already peaked with Chinese demand nearing its peak. And the bottom line is that if China peaks then global CO2 emissions are also close to peaking'😳 On my own brief a brief flyby - I'm particularly pleased to see data sets on battery storage, battery cells, and key minerals and materials...all of which I've been super focussed on tracking since 2019 (tips cowboy hat to Benchmark Mineral Intelligence & Co in that regard! 🤠) Bravo Energy Institute President Juliet Davenport & CEO Dr Nick Wayth CEng FEI FIMechE for bringing this all to us (with a little help from their friends!) - so on behalf of an audience I know will put the material to good use - THANK YOU! 👏 #energy #renewables #oilandgas #supplychain

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One week after the EU AI Act came into force, the UK 🇬🇧 is making strides to catch up on AI regulations. Keir Starmer is moving beyond Rishi Sunak’s voluntary approach to prioritise both safety and innovation. In my book, She Disrupts: A Black Woman’s Journey in STEM and AI Industries, I delve into the dangers of oppressive algorithms and their impact on Black women. Without proper representation, we risk replicating the same unconscious and unrealistic biases. As Condoleezza Rice once said, “What you know today can affect what you do tomorrow. But what you know today cannot affect what you did yesterday.” This underscores the importance of acting now to build equitable AI systems that will shape our future positively. For any organisation to effectively implement AI regulations and control what is built, they need comprehensive training and a diverse team with personal experiences that ensure the data captured meets the needs of their target audiences. It’s encouraging to see the new government thinking about legal safeguards to protect the public, especially Black women, from harmful AI applications. Three Takeaways from my book She Disrupts for Building an Equitable AI System. 1. We need diverse tepresentation in AI development. AI systems must be developed by diverse teams to avoid perpetuating existing biases. This ensures that algorithms are fair and equitable, reflecting a broad range of experiences and perspectives. 2. Organsations need robust training programs that emphasise ethical AI practices. This training should cover the social implications of AI and equip developers with the skills to build responsible AI systems. 3. To create AI systems that serve all segments of society, especially marginalises groups, it is crucial to collect and use data ethically. Understanding and mitigating biases in data ensures AI applications do not reinforce systemic inequalities. It’s a critical time for the UK to enhance its AI regulatory framework. By focusing on these key areas, we can ensure that AI systems are not only innovative but also equitable and responsible. Let’s drive this conversation forward and advocate for AI that truly benefits everyone. Links to the article is in the comments below 🔽🔽🔽🔽 #AI #EquityInTech #SheDisrupts #AIRegulation #TechForGood #BlackWomenInSTEM #innovation

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As the Chief Technology Officer at a Health startup using AI, I see the introduction of the "Artificial Intelligence (Regulation) Bill" as a critical juncture for the technology sector. This proposed legislation offers a chance to establish a regulatory framework that not only protects the public and maintains ethical standards but also encourages innovation. The creation of an AI Authority could serve as a centralised body to ensure consistency and coherence across various sectors, effectively addressing the current regulatory fragmentation. Such regulation is crucial to balance rapid technological advancements with the need for transparency and accountability, ultimately fostering a more trustworthy AI ecosystem. This bill could set a precedent for global AI governance, positioning the UK as a leader in this vital area. Lord Holmes #aibill #ArtificialIntelligence #startups #ai #ukai #aijobs

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This is a fascinating graph showing a stark change in how many applications there have been for care workers applying for visas to live and work in the UK. Care providers are as well recruited as they have been for years but how will this impact that?

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Half of UK SMEs use AI. 30% fear missing out. Where are you? SMEs are 99% of companies and half of economic output in the UK. (We're talking 2 to 249 employees). Almost half use AI. Most often this is one-off not top down or strategic. The older the business owner, the smaller the company and the further from London, the less likely AI is to be used. 30% of SMEs admit they are only adopting AI to keep up with the competition. That's a recipe for losing money. If you have a use case in mind and a 5-figure budget MSBC Group offers a free consultation about the best way to proceed. You might not even need AI to automate. If you do we have cost effective, custom and open source solutions already working on 3 continents. Drop me a line or chat with Priyank Bhavsar. Can you afford to be left behind? ----- Data from Be the Business

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