Discover and read the best of Twitter Threads about #deepmind

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Revolutionizing the World: 20 AI & Machine Learning Startups You Need to Know. 🧵...
1/20: In this thread i will try and explore the fascinating world of AI and machine learning startups! Discover some of the most innovative companies pushing the boundaries in this space. #AIStartups #MachineLearning
2/20: First up is @OpenAI, the team behind the groundbreaking GPT series.

With GPT-4, they're developing even more advanced natural language processing capabilities to revolutionize human-computer interactions. #NLP #OpenAI
Read 22 tweets
🧵🧵 THREAD: #Bioinformatics and #AlphaFold 🧵🧵
1. #AlphaFold is a deep learning system developed by #DeepMind, to predict the 3D #structure of #proteins from their #aminoacid sequence.
2. #AlphaFold has been applied and tested extensively in the biennial #CASP (Critical Assessment of protein Structure Prediction) experiment, and has achieved state-of-the-art performance.
Read 9 tweets
In the recent years @DeepMind has been working on Protein Folding and thanks to their deep learning architecture AlphaFold they already managed to predict millions of proteins, accelerating the making of new protein-based drugs for fighting diseases.  🧵

#DeepMind #AlphaFold #AI Image
When mutated, normal cells might become cancerous. AlphaFold may determine how a mutation can alter the structure, and hence the function, of the proteins encoded by these genes. Understanding how mutations influence their structure can be key to developing new medical treatments
AlphaFold, is able to predict the structure of the protein in which a mutation occurs, see where that mutation is, and how the mutated protein interacts with other molecules, and ultimately get an idea about the mechanism, or why that mutation causes a problem for that cell
Read 3 tweets
I’m at an interesting event today about #AI and the US military at the national press club ImageImageImage
Currently listening to the Co-founder of #Deepmind talking about reliability and error and AI… now the discussion is moving to implementation of ethical principles with #AI and Dr Jane Pinelis from JAIC.
Fascinating discussion- someone is asking how DOD can “measure trust” - this is interpreted as measuring ‘reliance’ - how much they can rely on technology. They also consider how human behaviour interacts ie how military use the technology, user behaviour with it. Image
Read 24 tweets
Daily Bookmarks to GAVNet 08/04/2021…
Place-based pathologies: economic complexity maps COVID-19 outcomes in UK local authorities…

#EconomicRecovery #PublicHealth #COVID19 #localities #mapping
DeepMind’s Vibrant New Virtual World Trains Flexible AI With Endless Play…

#DeepMind #VirtualWorld #ArtificialIntelligence #SkillsetDevelopment
Read 8 tweets
Last year I congratulated Demis Hassabis, a former chess prodigy who went on to astound the scientific community with his algorithms. His company, @DeepMind who research and build safe #AI systems, has now made a database of human protein structures freely available online.
It is said that scientists have only decoded the structure of a fraction of human proteins in "onerous" lab work, which begun in the 1950s. However, DeepMind's AI program, AlphaFold, has claimed to have predicted the structure of nearly all 20,000 proteins expressed by humans.
“I almost fell off my chair in just excitement and amazement that this longstanding problem of how proteins fold had been solved", Prof Ewan Birney, the director of the EMBL-EBI, working in partnership with the company.…
Read 5 tweets
30/11 > “Cela va tout changer” : l’#IA de #DeepMind fait un pas de géant dans la résolution des structures protéiques via @nature #LaMethSci Image
30/11 > Plus de 100 visons danois infectés se sont échappés et pourraient propager le #SARSCoV2 à la faune via @ScienceAlert #LaMethSci Image
30/11 > Un bébé est né avec des anticorps protecteurs après que sa mère ait eu la #CoVid19 pendant sa grossesse via @ScienceAlert #LaMethSci Image
Read 5 tweets
#Alphafold by #deepmind used solid interdisciplinary intuitions for algorithm/model design. It wasn't just a rinse-and-repeat machine learning exercise. Details on methods are limited, but here's my best interpretation (+some predictions) so far: [1/n]
Protein sequence databases provide us samples that have defacto passed the fitness test of evolution and are information-rich. "Genetics search" is a retrieval step to find nearest-neighbors as defined by sequence alignment. Why do we need nearest-neighbors (NNs), you ask?
There's a neat principle/intuition called coevolution that can help explain. The mutational variance observed can give clues to protein structure and function. Read more here:
Read 13 tweets
Fabio Ciucci on LinkedIn [1/8]: #Putin said "the nation that leads in #AI will rule the world," not that "a rebel AI will rule the world starting with burning the nation that built such AI." #ArtificialIntelligence
Fabio Ciucci on LinkedIn [2/8]: If #Russia and #China lead on weaponized AI (and they could), other nations including the USA (whatever they deny) do it too, like with atomic bombs.
Fabio Ciucci on LinkedIn [3/8]: News: Google AI (#DeepMind #AlphaStar) finally became able to kill every pro-human at #starcraft2 war game too.
Read 9 tweets

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