Video

thankyou

Yeah this video was predated 2020 collective effort on Twitter of initial working AI model that went viral for free? Each year that goes by hierarchy madness gets worse and worse because the people unwittingly greedily allowed an anonymous donor of methodology to dethrone all hierarchy all at once meaning king of kinds. Sad pathetic depraved people roam this earth looking for guidance it's not that hard to make a splash. Due respects all hail the peoples king the rest of you infinity print is for biggest cover up ever lies begit lies your gonna end up going to war with your children you know that right straight impass they think your crazy you know their crazy becauseyou did it to them letting crazy people lead never filling you in all you ask for is guidance if anyonehas to rule.

My favorite programming language is English

The ocaml user is clearly janestreet

Great questions 👍

Where is the data going to come from ? There are strict hippa regulations especially in USA

thank you so much for your help. i was able to load my custom YOLOv5 model on windows and it works perfectly. Im extremely grateful to you!

Great discussion. Concrete and accessible.

lol he doesn't give a fuck and it's awesome

Good Session.

Very interesting. I think the media hype is moving faster than the progress of AI's.

Fake accent is irritating can't focus what she is speaking

Great Talk. Indeed insightful as well.

LLM-based coding assistants are especially nice to those of us who habitually over-comment. My preferred programming language is .... English!

breath of fresh air, great talk

a lot of times, we want to believe agents will not replace the coder jobs it WILL replace the "coder job" that fills up rows of cubicles at large companies coders that feed into large bureaucracies of self-important software maintenance teams writing the same database/web application the same way as the last decade I think the actual coder jobs (at the front edge of software) and the new AI-native coder jobs are the things we want to protect and conserve

Weave can let you turn your inference budget into reliable data. 100% WandB = model insights

Hi, this video is HELPFUL and RATED 5/5 by me. But I wonder can I use custom dataset instead of the pre-set dataset as shown?

yes

Nice session

Thank you very much for this tutorial. I was easily able to follow and implement all of the steps. I'm really grateful to you

Excellent talk on Nvidia stack. The demo on NIM was good.

Great talk

Great talk. Really like the insights into the changes required as ML moves towards software developers.

Best tracking solution for years now. Keep it up

Where’s the rest of the video? 😢

The brain is not the mind The brain is not the mind The brain is not the mind Demis gonna win #DeepMind #EZ

Thanks for this. Professor Finn is a legend. I’ve been working through CS330.

Excellent questions by Lucas. Insighful discussion.

Should saturated benchmark be retired?

Guariscimi l aids l oids e u e la sindrome psichiatrica mi chiamo Biagio di balsamo

I fucking hate this guy. So full of himself and trying to be humble.

.. becoming comfortable with being uncomfortable ❤️

This is awesome.

❤

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As mentioned in a previous comment, a significant challenge in applying machine learning to drug discovery projects lies in the scarcity of robust and well-structured data. For instance, a major factor contributing to the failure of drug discovery endeavours is the suboptimal ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. The landscape could be transformed if we could develop models capable of predicting the outcomes of in vitro assays, allowing us to streamline the selection of well-optimized candidates for pre-clinical trials. However, the publicly available ADMET data is notably deficient in both quality and quantity, leading to the development of models that lack robustness.

Summary: Safety and size. The end.

Also 22:08 commenting on Lukas' question. The data in biological world are different from NLP or CV data in various ways, just to name a few: 1. In biology, the experiment data is only an estimation of the physical ground truth and often inconsistent, whereas in many other domain basically the test corpus used for model training is the same in training and real world. So the intrinsic noise within would impact the ceiling of how a model could be evaluated. Since the data is not ground truth, there is a greater gap between model output and reality, given even if the model is perfect on the testing data. 2. The lack of data is real. Partially because bio data is expensive. For CV an annotator could label a dozen or even a hundred pictures per hour and it costs less than $100. But in bio world, on average a single row of data could cost $100-$1000, even over $10k or more for things like protein structure, and takes days or weeks generate. It also requires high level expertise to conduct these experiments, and often repeats need to be done to analyze the intrinsic variances of these data. 3. The format of bio data is so diverse. For LLM, text is all you need, add voice and moving pictures we can train SORA. But in biology, there are hundreds of tasks, structure, affinity, stability, toxicity... each task has many different experiment types. Well. If you are interested in more about this my twitter is also NachuanShan. I work at BioMap as a data product manager, building protein language models.

20:27 cyberattackers watching this: "wtf I love ChatGPT now"

Great conversation. Love this topic.

What will be the SQLite of LLMs, with capability for local use? Llama?

Very insightful and informative

How silly is to redteam a model which you control the training data to check for bioweapons capabilities. How stupid should you have to be? Isn’t easier to run a search on the data 😂😅

How much did it cost to build, including hardware and engineering costs?

vin diesel!

There's a universe where Joseph Spisak is Mark Zuckerberg's brother. Oh, and nice presentation. Wonderful work they are doing at Meta AI.

My favorite fact from this is that the smarter the model, the more it violates rules. Just like us :)

Congratulations!