David Turban

Research Engineer @GoogleDeepMind. Applying machine learning to science. Physics background.

[David Turban @dhpturban]

@ycombinator @Zephyr_Fusion Cool concept! What's the plan for power capture and heat rejection?

It seems that both would have to be achieved with substantially less collector/radiator area than a solar array of equivalent power to make economic sense.

[Brendan McMorrow @brendanbc2]

At @GoogleDeepMind, our world-class team of quantum materials experts, engineers, and AI researchers is using massive-scale compute and AI to revolutionize materials discovery.

We're expanding! We are looking for truly exceptional computational materials scientists. 👇

[Joseph Krause @josephfkrause]

Congrats to @ekindogus, @draykol, and the entire @GoogleDeepMind team on a very interesting publication. The momentum is continuing to build in this field - the future of science is here 🔥

[Google DeepMind @GoogleDeepMind]

Starting 🔜 the @NobelPrize lectures featuring our laureates - CEO @DemisHassabis and Research Director John Jumper - who will discuss their award-winning work on protein prediction and the journey to building #AlphaFold.

Tune in to watch from 9:50am GMT → https://t.co/zORIWz8wzC

[Pushmeet Kohli @pushmeet]

The #AlphaFold 3 model code and weights are now available for academic use. We @GoogleDeepMind are excited to see how the research community continues to use AlphaFold to address open questions in biology and new lines of research.

https://t.co/kVB9hWJZTI

[Muratahan Aykol @draykol]

Excited to share our new paper “Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico Predictions” in @J_A_C_S. Exploratory synthesis is expensive and target prioritization is critical to improve chances of synthesis. https://t.co/ymdCyAx7hK

[The Nobel Prize @NobelPrize]

BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”

[Michael A. Arouet @MichaelAArouet]

German approach to fight climate change:

1. Close nuclear power plants

2. Keep coal mines and coal power plants going instead

3. Underreport coal mines emissions by factor of 184

4. Make energy intensive industries not profitable in the process

Genius, simply genius

[David Turban @dhpturban]

@TimMLatimer @CJHandmer @yishan @MikeDubrovsky How does it work? Genuinely interested. Naively, Casey's starting point seems pretty reasonable with my physics hat on.

[David Pfau @pfau]

I’m ending my Twitter break to share what I’ve been working on for the last two years - a new way to solve one of the most fundamental problems in quantum physics, computing excited states! https://t.co/0BxvatMrPB

[David Pfau @pfau]

OK, this is one I’ve been waiting to share for a *long* time – the first ever demonstration of deep reinforcement learning on a nuclear fusion research device! https://t.co/HVfUCrMTlM

[David Bowler @MillionAtomMan]

DeepMind join the DFT functional game: a "local range-separated hybrid" developed by deep learning which seems to produce excellent results #CompChem
https://t.co/ySTvBdiyR1

[David Turban @dhpturban]

Made a display piece out of my old XFX Radeon R9 390X @AMD @XFX_PlayHard

[Science Magazine @ScienceMagazine]

Neural networks can be used to build a more accurate map of the density and interaction between electrons than was previously attainable, new research from @DeepMind shows.

Learn more ⬇
#ScienceResearch: https://t.co/tLiFr1mBy7
#SciencePerspective: https://t.co/MkAFcNF1C5

[James Kirkpatrick @ja_kirkpatrick]

Credit to the amazing team: @brendanbc2 @algaunt51 @dhpturban @alexggmatthews @pfau @exp_n
read more: https://t.co/210kjrpluV

[Google DeepMind @GoogleDeepMind]

Here a neural network describes the density functional, training on data from high accuracy calculations & exact fractional electron conditions - w/ unprecedented accuracy on main group chemistry.

@ja_kirkpatrick @brendanbc2 @algaunt51 @dhpturban @alexggmatthews @pfau @exp_n /3

[David Turban @dhpturban]

Strange electrons indeed

https://t.co/JdJcWHRDfi

[Demis Hassabis @demishassabis]

Proud of our latest work applying AI to Quantum Chemistry published in @ScienceMagazine! The properties of materials largely depend on their electrons. We introduce a new SOTA functional DM21 (open-sourced) that can accurately model many types of molecules https://t.co/sVLKp5TxMW

[Anatole von Lilienfeld @ProfvLilienfeld]

Brilliant contribution from @DeepMind, @ja_kirkpatrick, Paula, Aron, David, and co-workers uniting #quantum with #machinelearning to push #DFT beyond wB97X for bond-dissociation, reaction barriers, charge transfer and spin-states. It's so exciting! Many hearty congratulations!

[Aron @lonepair]

Eat breakfast? Clear my todo list? No, there is the new @DeepMind DM21 exchange-correlational functional to read about #compchem https://t.co/aSM5tIA3WA