Let’s Talk Data 🗣️ Help shape how health data transforms care by becoming a patient public voice partner! 💼 Share diverse views & keep conversations patient-centric. Paid opportunities available:🔗 england.nhs.uk/get-involved/…

Our Group Chief Executive, @MCubbonNHS recently spoke to @health1tech about the vital role digital has to play in our new five year strategy He also spoke about how Hive, our EPR system, is delivering value for our patients Read more: htn.co.uk/2024/08/06/blog-un…

What a week! Anyone else possibly discover signs of microbial life from billions of years ago on a planet 140 million miles from Earth? No? Just me?

In response to today’s IT outage which has caused significant global disruption, we have published this statement, including advice on how to defend against phishing attempts 👇 ncsc.gov.uk/news/major-it-ou…

A study with @OUHospitals has found that an automated AI voice system enhances patient care after cataract surgery ➡️ imperial.nhs.uk/about-us/new… The AI-powered system calls patients to ask questions, understands their answers and identifies patients who may need review by doctors.

MyMFT is our patient healthcare app. 📱 💙💻 It connects you to your medical information at Manchester University NHS Foundation Trust hospitals. Learn more, and sign up today, at: mft.nhs.uk/the-trust/mymft #HealthcareinYourHands

⁦@InsideHealthCIO⁩ ⁦@MFT_MRI⁩ ⁦@MRI_ED⁩ #ExcellentVisitProjectRed #ExcitingForPatients&Staff

New AI Snake Oil essay: AI scaling myths Scaling will run out. The question is when. Full essay: aisnakeoil.com/p/ai-scaling-… Summary: Scaling laws only quantify improvements in next-word prediction, not emergent abilities. What matters is emergence, and it is not governed by any law-like behavior. There's a reasonable view that LLMs can't extrapolate too far beyond their training data. If so, at some point, having more data no longer helps because all the tasks that are ever going to be represented in it are already represented. Besides, there are limits to how much data companies can get. It's not that they'll "run out" of training data — there’s always more data, but it will cost more and more. Seemingly exponential tech trends have a tendency to suddenly flatline. Scaling is ultimately a business decision and fundamentally hard to predict in advance. Synthetic data is not magic. It has many great uses but increasing the volume of training data is not one of them. Self-play has been spectacularly successful in self-contained environments like Go but won't work everywhere. Based on current market trends, building bigger models is hard to justify because the barrier to adoption of current models isn't capability, it's cost and other factors. OpenAI, Anthropic, and Google have all made their frontier models much smaller recently, if we use API pricing as a rough proxy for size. Unlike dataset size and model size, training compute continues to scale (smaller models require more training to reach the same level of performance). The earlier crop of models were under-trained and the current generation is being trained for dramatically longer, which is better when accounting for inference cost. In the AGI chapter of the AI Snake Oil book (amazon.com/Snake-Oil-Artific…) we conceptualize the history of AI as a punctuated equilibrium, which we call the ladder of generality. Instruction-tuned LLMs are the latest step; an unknown number of steps lie ahead. Historically, standing on each step of the ladder, AI researchers been terrible at predicting how far you can go with the current paradigm, what the next one will be, when it will arrive, what new applications it will enable, and what the implications for safety are. That is a trend we think will continue. With @sayashk.

Finally admitted that age has defeated me and purchased varifocals. I do worry that I will be like the ED-209 from Robocop the first time I attempt stairs though.

🏆✨Congratulations to our Hive team! We're delighted our fantastic @MFT_Hive team have won the HSJ 'Digital Team of the Year' award! What a fantastic achievement! ✨🥇👏

I'M DOING A TALK TONIGHT Bad Science, data science, privacy, data infrastructure... and talking with generalists (policymakers and "the public")... about tricky technical issues and unwelcome truths. TELL YOUR FRIENDS eventbrite.co.uk/e/from-bad-…

We’re deeply saddened to learn of the death of our patron Rob Burrow CBE. Since his MND diagnosis in 2019, Rob has played a vital role in raising awareness and money to support our work. We will be forever grateful. Our thoughts are with Rob’s family, friends and fans.

We would like to wish Professor Jane Eddleston, Joint Group Medical Officer, a wonderful retirement after a dedicated career with MFT. Professor Jane Eddleston was the first female doctor to receive a prestigious national intensive care award. Happy retirement! 💙 👏

👑 💜 Royal News! We're delighted to share that Manchester Royal Infirmary has retained its royal patronage from the Royal Family as part of a celebration marking the anniversary of the Coronation of King Charles III and Queen Camilla. Read the story ➡️ bit.ly/4bGK2Dd

NEWS: New Maternity Early Warning Score to be implemented across the NHS @UniofOxford researchers develop a new system to identify signs of deterioration in pregnant women. medsci.ox.ac.uk/news/new-mat…

JOB: Director of Research, Institute for Ethics in AI, University of Oxford. Deadline: June 10th minervasearch.com/current-op…

🗞️ Groundbreaking cancer research at @MFTnhs is successfully identifying younger women at increased risk of breast cancer, after one year of opening 👏 The study launched in memory of late Girls Aloud singer, Sarah Harding and is led by @DrSachaHowell 👇 research.cmft.nhs.uk/news-ev…

After an amazing first two weeks in Manchester, this weekends plans are sitting outside in sunshine: while(gardenmusic) {    wine.drink();    nexttrack.execute();    if(wine == “empty”)    {      if(wineglass == “empty”         wineglass.topup();      wine.refill();     } }