Robocrunch        AI

Benedict Evans    @benedictevans   ·   9/14/2021
Cameras are still the one place where you can really see a difference in a new high-end smartphone each year, between the hardware and the computational photography. Night mode, depth of field, macro...
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Sara Hooker    @sarahookr   ·   9/10/2021
+ The overfitting of hardware to a small list of open source models: "This is also why you shouldn’t read too much into MLPerf’s results. A popular model running really fast on a type of hardware doesn’t mean an arbitrary model will run really fast on that hardware."
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Kai-Fu Lee    @kaifulee   ·   7/11/2021
Our latest AI vision portfolio and 1st investment in Europe @Prophesee_ai event-based sensors + software for machines. The latest breakthrough tech can be used in computational photography, autonomous driving, industrial automation, IoT, healthcare, etc.
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Weights & Biases    @weights_biases   ·   9/9/2021
New podcast episode! 📢 @l2k and @emilymbender dive into the problems with bigger and bigger language models, the difference between form and meaning, the limits of benchmarks, and the #BenderRule. 🎥: They discuss 4 of Emily's papers ⬇️ 1/5
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François Chollet    @fchollet   ·   6/26/2021
I really think that any agent that is self-directed (that can set its own goals, that has intent) must feature emotions (if only inwards ones). Emotions are the expression of the gap between one's situation and one's intent.
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David Pfau    @pfau   ·   8/28/2021
It boggles my mind that people in fields like computational biology took tools for low-D visualization and mistook them for having something scientifically meaningful to say. It's computational tea-leaf reading.
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Matt Goldrick    @MattGoldrick   ·   8/9/2021
Deadline Oct 15: Asst/Assoc prof, computational modeling , UCLA Psych
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Berkeley Linguistics    @BerkeleyLing   ·   9/3/2021
Congratulations to Alice Shen (PhD 2020), who has accepted a position as a computational linguist at Grammarly!
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Sara Hooker    @sarahookr   ·   9/10/2021
fantastic blog post by @chipro "With so many new offerings for hardware to run ML models on, one question arises: how do we make a model built with an arbitrary framework run on arbitrary hardware?"
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Gabriel Peyré    @gabrielpeyre   ·   12/5/2017
Computational Optimal Transport: the book. All you ever wanted to know about OT: theoretical insights, algorithms and applications!
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Petar Veličković    @PetarV_93   ·   6/18/2021
Happy to announce that EPMP has now been accepted at the #ICML2021 Workshop on Computational Biology! It feels great to come back to the venue that supported our (AG-)Fast-Parapred line of models three years ago, and we look forward to discussing our work with everyone!
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Roger Melko    @rgmelko   ·   9/14/2021
Looking forward to my talk at Quantum Many-Body Days 2021. Today's session is "Machine Learning and Computational Physics", with @fverstraete
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Tal Linzen    @tallinzen   ·   9/11/2021
Come be my colleague! "The search is open regarding subfield (e.g., developmental/acquisition, adult processing) and methodology (such as behavioral, neuroscience, computational approaches)."
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John Carlos Baez    @johncarlosbaez   ·   9/4/2021
Oh, whoops: the picture of the twisted cubic is from Alexander Kasprzyk's computational commutative algebra notes: and you can read more about the twisted cubic here: (8/7)
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DeepMind    @DeepMind   ·   6/17/2021
Our deep GNNs leverage recent DeepMind research such as BGRL (BYOL for graphs) & Noisy Nodes (denoising GNN regulariser). The hope is that this work can have an immediate impact on large-scale applications of GNNs, especially for social networks & computational chemistry. (2/)
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  Relevant People  

Benedict Evans
Trying to work out what's going on, and what happens next. Mostly tech. Past lives in equity research, strategy and venture capital. Yes, I have a newsletter.
Benedict Evans 62.4

Sara Hooker
Research @ Google Brain, model compression, robustness + interpretability. @trustworthy_ml Founder of data for good non-profit @deltanalytics.

Our team research and build safe AI systems. We're committed to solving intelligence, to advance science and humanity.
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Weights & Biases
Developer tools for machine learning. Build better models faster with experiment tracking, dataset versioning, and model management.
Weights & Biases 38.3

John Carlos Baez
I'm a mathematical physicist interested in saving the planet.
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Matt Goldrick
Linguistics and cognitive science. Opinions are my own. he/him/his
Matt Goldrick 24.0

Kai-Fu Lee
#AI Expert, CEO of 创新工场 @sinovationvc, former President of Google China, Author of AI 2041 and NYT Bestseller AI Superpowers
Kai-Fu Lee 60.6