Data Science by ODS.ai 🦜

2024-05-21 18:22:27 Images that Sound: Composing Images and Sounds on a Single Canvas

abs: https://arxiv.org/abs/2405.12221
project page: https://ificl.github.io/images-that-sound/
code: https://github.com/IFICL/images-that-sound

This paper introduces an inference-time procedure that generates images that are also spectrograms corresponding to the prompt. It uses a latent image and audio diffusion model with same latent space (Stable Diffusion v1.5 and Auffusion) and denoise the same latent with both.

@opendatascience Open / Comment

2024-05-08 22:54:57 AlphaFold 3 predicts the structure and interactions of all of life’s molecules

Google DeepMind представили Alpha Fold3, новую модель искусственного интеллекта, которая предсказывает структуру и взаимодействия молекул.

Благодаря точному прогнозированию структуры белков, ДНК, РНК и многого другого, а также того, как они взаимодействуют, наше понимание биологического мира может выйти на новый уровень, а в практическом применение поможет разработке новых лекарств.

Эта революционная модель, может предсказывать структуру и взаимодействия всех молекул жизни с беспрецедентной точностью.

На основе входного списка молекул Alpha Fold3 генерирует их общую трехмерную структуру, показывая, как они сочетаются друг с другом. Программа моделирует крупные биомолекулы, такие как белки, ДНК и РНК, а также небольшие молекулы, также известные как лиганды.

Кроме того, Alpha Fold3 может моделировать химические модификации этих молекул, которые контролируют здоровое функционирование клеток, нарушение которых может привести к различным заболеваниям.

Теперь для учёные со всего мира могут работать с AlphaFold 3 совершенно бесплатно.

Blog: https://blog.google/technology/ai/google-deepmind-isomorphic-alphafold-3-ai-model/
Nature: https://www.nature.com/articles/s41586-024-07487-w
Two Minute Papers:



@ai_machinelearning_big_data Open / Comment

2024-05-04 10:11:12 We followed on developing theme in Novemeber 2022. And it looks like we might have another attempt to renew our avatar, what do you think? Open / Comment

2024-05-04 10:11:06 For almost 5 years channel picture beared arbitrary picture found in google and now we updated it with a proper new channel logo generated by neural network. Do you like it? Open / Comment

2024-05-03 19:58:54 Say Goodbye to LoRA, Hello to DoRA

DoRA consistently outperforms LoRA with various tasks (LLM, LVLM, etc.) and backbones (LLaMA, LLaVA, etc.)

[Paper] https://arxiv.org/abs/2402.09353
[Code] https://github.com/NVlabs/DoRA

#Nvidia
#icml #PEFT #lora #ML #ai

@opendatascience Open / Comment

2024-04-27 08:12:21 Discover, download, and run local LLMs

LM Studio allows to run #LLM model of your choice locally

Link: https://lmstudio.ai/ Open / Comment

2024-04-18 20:44:20 Llama 3 is here, with a brand new tokenizer!

Вышла Llama 3

Meta выпустила новую SOTA Llama 3 в двух версиях на 8B и 70B параметров.

Длина контекста 8К, поддержка 30 языков.

•HF: https://huggingface.co/spaces/ysharma/Chat_with_Meta_llama3_8b
•Blog: https://ai.meta.com/blog/meta-llama-3/

Вы можете потестить MetaLlama 3 70B и Meta Llama 3 8B с помощью бесплатного интерфейса: https://llama3.replicate.dev/

@ai_machinelearning_big_data Open / Comment

2024-04-12 11:17:06 ControlNet++: Improving Conditional Controls
with Efficient Consistency Feedback

Proposes an approach that improves controllable generation by explicitly optimizing pixel-level cycle consistency

proj: https://liming-ai.github.io/ControlNet_Plus_Plus/
abs: https://arxiv.org/abs/2404.07987

@opendatascience Open / Comment

2024-04-09 11:06:13 PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Significantly improved finetuned perf by simply changing the initialization of LoRA's AB matrix from Gaussian/zero to principal components.

On GSM8K, Mistral-7B fine-tuned with PiSSA achieves an accuracy of 72.86%, outperforming LoRA’s 67.7% by 5.16%.

Github: https://github.com/GraphPKU/PiSSA
Paper: https://arxiv.org/abs/2404.02948

@opendatascience Open / Comment

2024-04-02 16:00:16 Position: Analyst/Researcher for AI Team at Cyber.fund

About Cyber.fund:
Cyber.fund is a pioneering $100mm research-driven fund specializing in the realm of web3, decentralized AI, autonomous agents, and self-sovereign identity. Our legacy is built upon being the architects behind monumental projects such as Lido, p2p.org, =nil; foundation, Neutron, NEON, and early investments in groundbreaking technologies like Solana, Ethereum, EigenLayer among 150+ others. We are committed to advancing the frontiers of Fully Homomorphic Encryption (FHE) for Machine Learning, privacy-first ML (Large Language Models), AI aggregations, and routing platforms alongside decentralized AI solutions.

Who Are We Looking For?
A dynamic individual who straddles the worlds of business acumen and academic rigor with:
- A robust theoretical foundation in Computer Science and a must-have specialization in Machine Learning.
- An educational background from a technical university, with a preference for PhD holders from prestigious institutions like MIT or МФТИ.
- A track record of publications in the Machine Learning domain, ideally at the level of NeuroIPS.
- Experience working in startups or major tech companies, ideally coupled with a background in angel investing.
- A profound understanding of algorithms, techniques, and models in ML, with an exceptional ability to translate these into innovative products.
- Fluent English, intellectual curiosity, and a fervent passion for keeping abreast of the latest developments in AI/ML.

Responsibilities:
1) Investment Due Diligence: Conduct technical, product, and business analysis of potential AI/ML investments. This includes market analysis, engaging with founders and technical teams, and evaluating the scalability, reliability, risks, and limitations of products.

2) Portcos Support: Provide strategic and technical support to portfolio companies in AI/ML. Assist in crafting technological strategies, hiring, industry networking, identifying potential project challenges, and devising solutions.

3) Market and Technology Research: Stay at the forefront of ML/DL/AI trends (e.g., synthetic data, flash attention, 1bit LLM, FHE for ML, JEPA, etc.). Write publications, whitepapers, and potentially host X spaces/streams/podcasts on these subjects (in English). Identify promising companies and projects for investment opportunities.

How to Apply?
If you find yourself aligning with our requirements and are excited by the opportunity to contribute to our vision, please send your CV to sg@cyber.fund. Including a cover letter, links to publications, open-source contributions, and other achievements will be advantageous.

Location:
Location is flexible, but the candidate should be within the time zones ranging from EET to EST (Eastern Europe to the East Coast of the USA).

This is not just a job opportunity; it's a call to be part of a visionary journey reshaping the landscape of AI and decentralized technology. Join us at Cyber.fund and be at the forefront of the technological revolution. Open / Comment