Jony Ive is collaborating with OpenAI CEO Sam Altman on a new AI
hardware project. The venture could raise $1 billion by year-end
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TLDR
TLDR AI 2024-09-23
🚀
HEADLINES & LAUNCHES
CONTEXTUAL RETRIEVAL (12 MINUTE READ) [4]
Anthropic shows how to semantically chunk documents, which
dramatically improves performance while only costing $1/million chunks
due to caching.
PROMPTING O1 (6 MINUTE READ) [5]
This guide was missed in the excitement of OpenAI’s new reasoning
models. It shows how prompting this new model is different and
requires simpler prompts and a more structured input context.
JONY IVE CONFIRMS HE’S WORKING ON A NEW DEVICE WITH OPENAI (2 MINUTE
READ) [6]
Jony Ive is collaborating with OpenAI CEO Sam Altman on a new AI
hardware project. The venture could raise $1 billion by year-end and
involves key former Apple designers. Specifics of the device remain
undetermined, but it aims to leverage generative AI for advanced user
interactions.
🧠
RESEARCH & INNOVATION
FINE-TUNING IMAGE-CONDITIONAL DIFFUSION MODELS IS EASIER THAN YOU
THINK (24 MINUTE READ) [7]
Much work has been done to generalize pretrained image diffusion
models into niche depth estimators and other image conditional models.
This work found that by simplifying the problem and fixing a small
bug, researchers were able to get substantially improved performance
with less training compute.
TRAINING LANGUAGE MODELS TO SELF-CORRECT VIA REINFORCEMENT LEARNING
(32 MINUTE READ) [8]
Deepmind has released a paper that shows promise, even if the actual
results aren’t state-of-the-art. It shows a reinforcement learning
paradigm that can be used to help models self-correct when generating
math and code.
MICHELANGELO: LONG CONTEXT EVALUATIONS BEYOND HAYSTACKS VIA LATENT
STRUCTURE QUERIES (21 MINUTE READ) [9]
Another great Google paper that shows how to evaluate long context
models. It is directionally similar to the recent work by Magic.
🧑💻
ENGINEERING & RESOURCES
WEBINAR: HOW ANALYTICS INDUSTRY LEADERS ARE MODERNIZING DATA TEAMS
(SPONSOR) [10]
This Wednesday [10], data leaders from Bayer, Evoke, and AtScale will
discuss:
* Deciding between centralized, decentralized, and hybrid data teams
* Data maturity assessments and data quality assurance
* Effective data cataloging and lineage
Attend live to join the discussion! Save your spot here [10]
3D TOPIA WITH DIFFUSION TRANSFORMERS (GITHUB REPO) [11]
Image and text to 3D with mesh smoothing and PBR ready lighting
AI FOR JQ (GITHUB REPO) [12]
Simple yet powerful tool to label, embed, and classify unlabeled text
at the command line. It also works on streams which gives it the
ability to receive piped input from other sources.
KYUTAI LABS RELEASES MOSHI WEIGHTS (GITHUB REPO) [13]
The highly funded real-time assistant voice startup showed off its
impressive tech a few months ago. It has now released a detailed
technical report and several model artifacts including code and model
weights.
🎁
MISCELLANEOUS
MOST POWERFUL LLM ON A SINGLE GPU (12 MINUTE READ) [14]
Solar Pro is a 22B language model that can fit on a single 80GB GPU.
The goal of this project is to make the most powerful model that can
run on a single device.
STUDY REVEALS AI ISSUES IN HOME SURVEILLANCE (9 MINUTE READ) [15]
Researchers find large language models make inconsistent decisions
about whether to call the police when analyzing surveillance videos.
SAE INTUITIONS (18 MINUTE READ) [16]
Sparse Autoencoders are the number one tool used today to understand
the internals of language models. This post explores the intuitions
behind the models and some good information on how they work.
⚡
QUICK LINKS
GENERALIZED KNOWLEDGE DISTILLATION TRAINER (HUGGING FACE HUB) [17]
The TRL library has added GKD to its training procedures.
ARCADE AI WITH $17M RAISED LAUNCHES PRODUCT CREATION PLATFORM (2
MINUTE READ) [18]
Arcade is a new platform where users can go from prompt to product.
SALESFORCE TAPS NVIDIA TO DEVELOP AI-POWERED AVATARS (4 MINUTE READ)
[19]
Salesforce is collaborating with Nvidia to create AI-powered avatars
designed to enhance virtual interactions and customer service.
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Andrew Tan & Andrew Carr
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[4] https://www.anthropic.com/news/contextual-retrieval?utm_source=tldrai
[5] https://links.tldrnewsletter.com/A2uZqD
[6] https://www.theverge.com/2024/9/21/24250867/jony-ive-confirms-collaboration-openai-hardware?utm_source=tldrai
[7] https://arxiv.org/abs/2409.11355?utm_source=tldrai
[8] https://arxiv.org/abs/2409.12917?utm_source=tldrai
[9] https://arxiv.org/abs/2409.12640?utm_source=tldrai
[10] https://www.atscale.com/resource/modernize-data-teams/?utm_medium=email&utm_source=tldr&utm_campaign=20240925wbr&utm_content=webinar&utm_term=null
[11] https://github.com/3DTopia/3DTopia-XL?utm_source=tldrai
[12] https://github.com/taylorai/aiq?utm_source=tldrai
[13] https://github.com/kyutai-labs/moshi?utm_source=tldrai
[14] https://www.upstage.ai/products/solar-pro-preview?utm_source=tldrai
[15] https://news.mit.edu/2024/study-ai-inconsistent-outcomes-home-surveillance-0919?utm_source=tldrai
[16] https://adamkarvonen.github.io/machine_learning/2024/06/11/sae-intuitions.html?utm_source=tldrai
[17] https://huggingface.co/docs/trl/gkd_trainer?utm_source=tldrai
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