AI/ML Digest | Issue 36

AI/ML Digest | Issue 36

Hey and welcome to the latest edition of the Innovations in AI/ML Digest, brought to you by Roosh Circle!


Before we explore the latest in AI advancements, check out our upcoming events:

  • May 23, offline in Berlin: a meetup for product managers "Innovate & Execute: PM Stories from Startups". Register on Lu.ma.
  • May 30, Papers Club, online: "“Automating Software Regression Testing through Log Analysis" with Yassine Elhallaoui. Register here.

See you there! Now, back to the digest ↓

1/4 Get 32x faster performance on your vector search at only a 4% cost in accuracy

In their blog post, 极纳科技 show you how to get dramatically faster vector search by reducing them to binary digits, at a small cost in accuracy of retrieval.

Read it here: https://cutt.ly/iettC0lJ

2/4 英伟达 just made Pandas 150x faster with zero code changes

The upgrade is now available on Google Colab, allowing users to leverage the RAPIDS library for accelerated performance, whether on GPU or CPU.

Try it here: https://cutt.ly/LettNSQm

3/4 OpenAI announces GPT-4o

GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs.

Full release: https://cutt.ly/2ett1FQM

4/4 A new research paper by 谷歌

"Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?" is crucial for understanding how to safely implement new knowledge without compromising the integrity of the information.

Access paper: https://cutt.ly/oett25cZ


1/5 Last week was a monumental moment for AI startups as they collectively raised over $1 billion in funding

Among these, nine startups are at the forefront, keep an eye on these innovators: https://cutt.ly/jett8lux

2/5 Meet Bend, a high-level programming language for GPUs

With Bend you can write parallel code for multi-core CPUs/GPUs without being a C/CUDA expert with 10 years of experience. It feels just like Python. No need to deal with the complexity of concurrent programming: locks, mutexes, atomics... any work that can be done in parallel will be done in parallel.

Try it here: https://cutt.ly/Bett7x2u

3/5 You can now generate production-ready prompts in the Anthropic Console

Describe what you want to achieve, and Claude will use prompt engineering techniques like chain-of-thought reasoning to create more effective, precise and reliable prompts.

Try it here: https://cutt.ly/oett62kL

4/5 Build an autonomous research assistant with LangGraph and GPT Researcher

See a step-by-step walkthrough on how flow engineering and multi-agent collaboration can help automate in-depth research on any given topic — from architecture to run.

Try it out: https://cutt.ly/setywlTN

5/5 Introducing ScrapeGraphAI, a new tool that simplifies web scraping using LLMs

This Python library has become a go-to for its effectiveness in extracting information, compatible with ollama and other LLM providers, offering a streamlined solution for data extraction tasks.

GitHub: https://cutt.ly/XetyenQP


1/6 Say hello to create-llama, a single CLI command

Build a full-stack RAG app with next level citations: expand into a native pop-out PDF viewer.

GitHub: https://cutt.ly/BetyJCuv

2/6 Full Stack Transformer Inference Optimization Season 2: Deploying Long-Context Models

From hardware to MLsys, from modeling to user preference, this blog post discusses challenges in serving long-context models from production-level first hand insights.

Read it here: https://cutt.ly/UetyLSdg

A concurrent programming framework for serving multiple long-context user requests under limited GPU HBM size.

3/6 Improvements to data analysis in ChatGPT

Interact with tables and charts and add files directly from Google Drive and Microsoft OneDrive.

Details: https://cutt.ly/LetyNbw5

4/6 Take your personal AI assistants anywhere on the Internet with Zapier Central’s Chrome Extension

Chat with any web page, summarize and transform content and take action in 6,000+ apps like Google Sheets, Slack and Shopify—all without leaving your current tab.

Install: https://cutt.ly/Qety1SGp

5/6 Google DeepMind is advancing medical AI with Med-Gemini

The company has presented two recent research papers in which they explored the possibilities of Gemini in the healthcare space and introduced Med-Gemini, a new family of next-generation models fine-tuned for the medical domain.

Read here: https://cutt.ly/lety2GUt

6/6 Alignment Labs releases high-quality datasets and innovative training methods.

With over 3 million samples and a combination of pre-training, SFT, and RL, these new resources are set to significantly contribute to the AI field, enhancing model training and development.

More info: https://cutt.ly/wety3rsV


1/3 Podcast: "MVPs are officially dead: here's how to launch and find market fit in 2024"

Listen to a conversation between Sachin Rekhi and Tuomas Artman , co-founder of Linear , hosted by Fareed Mosavat .

Podcast link: https://cutt.ly/XetuuFUz

2/3 Hugging Face celebrates 100k on GitHub

This milestone is a testament to ML's reach and the Hugging Face's community's will to innovate and contribute. To celebrate, they highlighted 100 incredible projects in transformers' vicinity.

See the list here: https://cutt.ly/hetupzhT

3/3 Opinion: summer is a great time to boost your AI skills, and here's an 11-step LLM study plan to guide you

From data pipelines to tokenizer training with Karpathy's insights, it's a comprehensive roadmap for AI enthusiasts looking to enhance their expertise. Thank you for the plan, Sebastian Raschka, PhD .

See all 11 steps: https://cutt.ly/vetuaJEZ

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