David Walliker

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/g…

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/blo…

@rs_fullerton @RachelBurnham The world isn’t ready for that level of bin bants.

Tell you what’s a far bigger part of my life now than I’d ever imagined? BINS. I have four (4). I have a calendar appt to remember to take the right ones out at the right time. I think about “if it’s a good time to go to the tip” *constantly*.

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?

@RachelBurnham @MFTnhs Welcome to the team Rachel!

Relocation ✅ Off to be the new girl @MFTnhs this morning.

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-…

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

@rs_fullerton @Sonos @AppleMusic @oliviarodrigo @CrowdedHouseHQ @foofighters @taylorswift13 See - i will nod approval. I was going to Wembley to watch Taylor Swift but couldn’t only get 2 tickets and didn’t fancy being killed by one of the other 2 girls. Will approve 100% of foo’s. Crowded House would be in my top Antipodean bands, and Vampire is on the play list!

@rs_fullerton @Sonos @AppleMusic I don’t have one. But I have a top one of the ‘phonics. I mean to be fair, my top 50 wouldn’t have Coldplay in there. That’s the thing with music, it’s subjective. Love what you love. But you’re wrong with CP 😉

@rs_fullerton @Sonos @AppleMusic It’s pushing Coldplay down so you can listen to much better music. Call it a public service.

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

@GaryMcAllister Build our own? Goodness no.

WhatsApp use in the NHS?... I support it if used sensibly - but not for patient data. Teams doesn't cut it and specialist apps don't seem to have scaled. Should the NHS build their own?

@digitalhealth2 Edit: SIX YEARS ago.

@digitalhealth2 digitalhealth.net/2018/03/liverp… FIVE YEARS ago. So if we still need to explore this, something’s wrong with the navigation.

A one-million-pound project will explore how 5G technologies can improve and speed up the delivery of healthcare services in the North East of England. Read in full 👉ow.ly/IpWP50SxO0J

@GaryMcAllister Yes.

I wonder if I'll ever see an electronic voting system in my lifetime ...

@PaulJBtW @FD_DSM1 Is this like flu jabs, if it wasn’t on social media it didn’t happen….

Standard polling day selfie - delivering our constitutional right! Taking part is so important in a democratic society @FD_DSM1

⁦@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-m… 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-Arti…) 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.