Ellie Sleightholm

techUK & FutureDotNow rightly are raising alarm over workforce readiness for AI. The future of work will be AI-enabled. Whilst discussions around the impact of AI on work often focus on machines replacing humans, the reality is that humans will increasingly work alongside machines and AI in the future workplace. #BridgeDigitalDivide #WorkforceReadiness

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Tech enthusiasts love to wax lyrical about how AI could boost efficiency and cut costs in practically every industry under the sun — but in many ways, few could do with a sprinkling of AI magic more than healthcare. Beset by workforce shortages, rising costs as well as the strains of treating growing and ageing populations, the global healthcare sector has come under increasing pressure over the past few years. Many industry watchers point to the potential of AI to lend a helping hand — and the UK government seems to have the same line of thinking. Over the past few years, the NHS has been increasing its investment in AI. In 2019, the government announced it would invest £250m into a new NHS AI Lab to help tech companies develop and trial their tools in clinical settings. But despite the growing number of startups looking to deploy and trialling AI tools in the NHS, few have so far managed to secure commercial contracts with the organisation.    I found out exactly where startups are looking to deploy AI in the NHS — and the hurdles they face rolling out their products. Featuring: Peter Kecskemethy & Sarah Justine Kerruish — Kheiron Medical, Dr Dom Pimenta M.D. — TORTUS, Tom Searle PhD — CogStack and Greta Anderson — Balderton Capital. https://lnkd.in/eCBd4d5r

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Following on from my post on vectorising Wikipedia yesterday, here's a blog containing links to the files. Have fun with it, and let me know if you find any interesting uses for the data!

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AI has the potential to address some of humanity's most pressing problems — but only if everyone has the tools to build with it. That's why earlier this year we introduced Gemma, a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. We’ve continued to grow the Gemma family with CodeGemma, RecurrentGemma and PaliGemma — each offering unique capabilities for different AI tasks and easily accessible through integrations with partners like Hugging Face, NVIDIA and Ollama. Now we’re officially releasing Gemma 2 to researchers and developers globally. Available in both 9 billion (9B) and 27 billion (27B) parameter sizes, Gemma 2 is higher-performing and more efficient at inference than the first generation, with significant safety advancements built in. In fact, at 27B, it offers competitive alternatives to models more than twice its size, delivering the kind of performance that was only possible with proprietary models as recently as December. And that’s now achievable on a single NVIDIA H100 Tensor Core GPU or TPU host, significantly reducing deployment costs.

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📚🔬 Revisiting My PhD Journey with NotebookLM! 🎓⚡ Just explored NotebookLM on my PhD thesis: "Essays on Risk and Profitability in the Future British Electricity Industry" 🇬🇧💡 Key takeaways: Amazed at how well it captures nuances 🧠✨ Brings back memories of the research grind (and breakthroughs!) 💪🔍 Fascinating to hear my work come alive 🎧🗣️ Want to experience it yourself? Check it out: 🔗 https://lnkd.in/eabdGCdf #PhDLife #ResearchTech #AI #EnergyEconomics #NotebookLM

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𝗦𝗲𝗻𝗶𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 – 𝗗𝗶𝗳𝗳𝘂𝘀𝗶𝗼𝗻 𝗠𝗼𝗱𝗲𝗹𝘀 𝗕𝗿𝗶𝘀𝘁𝗼𝗹/𝗟𝗼𝗻𝗱𝗼𝗻 𝗨𝗽 𝘁𝗼 £𝟭𝟬𝟬𝗸 ▪ Revenue-generating AI start-up. ▪ Unique product with AI at its core. ▪ Recently raised multi-million ££ funding to support the next growth phase. Bristol is crying out for more AI companies so I’m buzzing to be supporting the latest player in this space. I’ve got two roles, one of which is more research based so I’m looking to speak with Machine Learning Engineers and Researchers with a solid understanding of diffusion models. The ML Engineer needs to have strong production experience and come from an image-based background. Diffusion model experience is the icing on the cake, but the client is aware there’s a limited number of people who will have experience taking these into production. Essentially, if the researcher has the required diffusion model expertise, then it’s less important for the engineer. There is a world whereby we can hire 2 x ML Engineers in place of a researcher, so long as the diffusion model experience is covered. 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: ▪ 0-1 experience is preferred – failing that, experience within an AI startup and the ability to wear many hats. ▪ Strong computer vision background, ideally diffusion models or transformers at the very least. ▪ ML production, pipeline and infrastructure (design and build). ▪ Understanding of MLOps principles. The engineer position needs to be at the senior level, but the researcher is more flexible. As an ML Engineer, you’ll essentially be the subject matter expert, so you’ll need experience in designing and building ML systems and infrastructure from scratch. This could in time turn into a leadership position depending on your career aspirations but it’s not a deal breaker if you want to remain an IC. The preference is to build the team in Bristol but there is scope for those in London to apply as long as you’re happy with monthly travel to Bristol. If you’re based in Bristol, then it will be 3 x days a week in the office. Unfortunately, sponsorship is not available for either position. #AI #artificalintelligence #diffusionmodel #diffusionmodels #machinelearning #ML #mlengineer #aiengineer

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I read an interesting article on the BBC News website this morning so decided to blog about it on my personal blog. I pasted the URL in and hit go! Seconds later I had a completely original version, so I edited it into my own voice and got sBlogIt! to create the images, audios and social media for it. And here it is ... https://lnkd.in/eD4a8TJa Want to be able to create blog posts in minutes? #sBlogIt!

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Open Source is a critical topic that has been largely overlooked in the UK Government's discussions around AI. By emphasizing open source, we have the potential to significantly enhance domestic initiatives such as the NHS and Manufacturing, as well as bolster our global presence as a technological innovator. If you believe in the importance of this issue, consider signing OpenUK's manifesto to ensure it becomes a key part of the conversation.

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Yesterday, I ran our first "Watch Me Viz" session internally for Lloyds Banking Group's Data Summer School (just like Andy Kriebel's Watch Me Viz livestreams!) 🌿 Find out which traits are most attractive in a romantic partner 🌹 Viz: https://lnkd.in/eBdnx-UB It was great to share my approach and design process live within the hour, and I was so pleased that people found the session useful! :) 💭 Although I wish I had more time for formatting during the session, it shows that even dedicating just one hour to practice your skills / exploring new datasets helps. Plus, you can always go back and improve these in your spare time! That's 1/3 down, excited for Max Griffin's and Ant Pulley's Watch Me Viz next! 💚🌟 Here's my refined version with extra formatting, and my 1-hour version below (comments). #MakeoverMonday #DataSummerSchool #LBGVizWiz Tableau #datafam #dataviz #survey #data #romance #love #tableau

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Post 1b/n: more reflections on working and parenting, from 1yr in the Data Science Campus. The other week, Richard Grove very kindly shared a blog on his experience of balancing parenting and running his own business, where he highlights four key insights: https://lnkd.in/ey6MPEF9 1: Productivity hacking. I’ve not gone down that route as such, but I definitely recognise the need very extreme prioritisation! I may have to try some more organised frameworks. Are you still looking for a buddy for the Cal Newport Deep Life Stack? 2: Work on things that matter. The opportunity cost for my time is so much higher now, which definitely reflects some of the conversations I’ve had with Mary Gregory and others about this. The challenge or tension I find personally on this (and your previous point) are the situations where a lot of the value I (think) I add is by giving myself space to be thoughtful and join things up - I find it challenging to time box. And my role means I get derailed a lot. So it goes. 3: Emotions at work/home are the same. I’ve got a different emotional constitution to you! (Obviously… :)) I’ve often had the opposite problem, that I need to give myself the option to react quickly rather than take time and take the calm long view. But I really recognise leaning against the ‘jerk response’ (I can feel it bubble up!), and learning to work with people where they are as quickly as you can. 4: Lean into new behaviours. What choice to we have? I like to think I have a deep well of experiences to draw on and help balance me… :-) And thanks for linking to Gemma Cameron’s blog - that really resonated with me too!

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I'm carrying on with my studying to become a certified expert in AI Ethics at a consultancy level, with #AlanTuringInstitute. It's been a strange couple of weeks as I see businesses being sold off the shelf AI solutions, with little follow up - to those exclaiming that they are AI experts as they have read a couple of books on AI. What really baffles me is that I still receive negative comments from my colleagues across my current industry that they don't know why I pursue digital transformation and AI and Machine Learning studies? AI and Machine Learning is quietly moving into every corner of our economy, causing disruption to our 20th century lived lives. I was reading this article and thought how apt the above narrative was. We are not dealing with a new piece of software we are going through the 4th Industrial Revolution - with the beginnings of intelligence far greater than our own. It really is worth taking those in the know seriously! "Across the nation, judges, probation and parole officers are increasingly using algorithms to assess a criminal defendant’s likelihood of becoming a recidivist – a term used to describe criminals who re-offend. There are dozens of these risk assessment algorithms in use" . 

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AI & Partners - How does the UK intersect with EU in terms of #AI regulation? This ground-breaking report from OpenUK helps to shed light on a question of growing significance. With EU #AI Act implementation imminent and questions of its extra-territorial nature front and centre, business leaders can benefit from these expert insights. Check out the post below for details. #AI

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SEIS/ EIS cheatsheet for Founders (If you want to have a chat for guidance on this, DM me. We've recently successfully been approved for this scheme, and completed our Seed funding round) EIS qualifying criteria and limits - https://lnkd.in/eCNWny3z SEIS qualifying criteria and limits - https://lnkd.in/e82gefXX You can apply to qualify for both SEIS and EIS at the same time, so might as well go for both For your application and paperwork, I would recommend SeedLegals. They have a brilliant online portal you can use, as well as experts on hand to guide you throughout your process. Charges are reasonable too. For employees, you should look at EMI Share Options, which allows you to give employees a part of the company via options where you can set the rules, plus extremely tax efficient for them. For NEDs, you can do Unapproved Share Options, again you can set the rules but with less of a tax advantage. Typically you would give NEDs 0.5-1% to act as your NEDs in the first year. For both, Seedlegals can arrange all paperwork for you via their online portal. To raise, you can use sites like Crowdcube & Seedrs, but be aware they do charge a fee, normally as a % of the raise. There are also a ton of SEIS/ EIS VC firms that are always looking to invest, but they're a lot more involved in the day-to-day operation. VC's are great if you need that structure and guidance. Alternatively, you can raise from your network. Look for people earning £150k+, as the tax advantages for those individuals are very good indeed, and they tend to already be investing in such deals and have a portfolio of them, and hence understand the risk and timelines involved.

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Rory Cellan-Jones kickstarts his AI in the NHS series. The focus and hype around AI - in the NHS or elsewhere - can sometimes be misplaced. AI can absolutely improve things for patients and healthcare professionals. Used pragmatically, it could have a transformative impact on the structural capacity problems in the NHS. The key is focusing on scalable interventions, allowing people to focus on what people are good at - caring for each other. We're reducing did not attends, and helping the most vulnerable patients using prediction algorithms within our patient engagement platform. Staff can use this to identify potential missed appointments and plan accordingly. Clinics run better and patients who need help are more likely to get it. I encourage everyone to read our conversation on Rory's Substack. Looking forward to seeing the next edition of the series! https://lnkd.in/eHaStpHt #healthtech #aiinthenhs #healthcare #futureofoutpatients

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Oxfordshire friends, I highly recommend the Oxford Geek Nights (OGN) meetup. There’s always an intriguing mix of speakers and subjects. At this week’s event I learnt: ·       The difference between bits and qubits (it’s to do with quantum computing). ·       How Dungeons & Dragons can make you a better manager. ·       That one of the speakers has created “video games” that don’t have screens (but do have flashing buttons, and slime). ·       That the relationship between “mechanical sympathy” and engineering can be a useful analogy in other scenarios. ·       That UK law says computers are reliable (this, in the context of the Post Office Horizon scandal - cue hollow laughter from assembled techies). ·       Why Oxford's area code is 01865. Fun, informative and interesting.

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I can't explain enough how fantastic this section was, we learnt about many interesting topics, such as Schemas: How should my data be organised logically? Normalisation: Should my data have a minimum of dependency and redundancy? Views: Which joins will be made most often?  - Non-Materialized  - Materialized Access control: Should all data users have the same level of access?  - GRANT and REVOKE ROLE  - CREATE OR REPLACE ROLE DBMS: How do I choose between all the SQL and noSQL options?  - NoSQL  - SQL and more! The course was very enjoyable and I highly recommend it. #DataScience #DataAnalysis #DBA DataCamp

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