Welcome back AI enthusiasts!
In todayās AI Report:
š¦ŗElon Muskās xAI Supercomputer Project
š§Googleās āAI Overviewsā Meltdown
šByteDanceās G-DIG Method for Data Selection
š 5 Trending Tools
š°Venture Capital Updates
š¼Whoās Hiring?
Read Time: 3 minutes
šRECENT NEWS
XAI
š¦ŗElon Muskās xAI Supercomputer Project
Image Source: Simon Walker/No. 10 Downing Street
Elon Muskās xAI startup reportedly plans to build a massive supercomputer to support Grok-1.5 and future AI projects.
Key Details:
The supercomputer will leverage over 100,000 Nvidia H100 GPUs to develop trillion-parameter language models and accelerate AI workloads.
Musk refers to the supercomputer as the āGigachad of Compute,ā planning to partner with Oracle and have it operational by Fall 2025.
Musk aims to leverage the supercomputer to build expansive GPU clusters to improve parallel processing tasks.
Parallel processing refers to breaking down complex calculations involved in training AI models into smaller, independent chunks that can be tackled simultaneously.
By clustering multiple GPUs together, xAI achieves a significant boost in processing power, allowing future AI projects to be trained on larger datasets in a shorter period of time.
The supercomputer will train future iterations of Grok-1.5: xAIās latest open-source conversational chatbot that showcases enhanced reasoning capabilities and can process longer and more complex prompts up to 128K tokens.
Why Itās Important:
AI models thrive on data. The more data an AI model is trained on, the better it performs. However, processing and analyzing massive datasets strains traditional computational resources.
Greater computing power allows AI models to handle vast amounts of data efficiently, leading to more accurate AI models with faster processing and analysis.
š§Googleās āAI Overviewsā Meltdown
Image Source: Canva AI Image Generator
Googleās new āAI Overviews,ā a feature that provides AI-generated summaries at the top of Google Search results, is facing backlash after generating bizarre and inaccurate summaries.
Key Details:
āAI Overviewsā rolled out last week after the Google I/O 2024 developer conference. It was added above standard Google Search results to offer more streamlined access to answers.
āAI Overviewsā started generating false and misleading summaries such as suggesting eating rocks, recommending running off a cliff, and supporting smoking while pregnant.
Google spokeswoman Lara Levin stated that the vast majority of āAI Overview queries resulted in high-quality information. Many of the examples weāve seen have been uncommon queries.ā
Why Itās Important:
Google is reportedly working on manually disabling āAI Overviewsā for specific Google Search results involving medical questions, recipe ideas, and committing crimes.
Earlier this year, Google Geminiās image generation tool refused to depict historically accurate results of Vikings, Nazis, and the Pope.
āGoogle doesnāt have a choice right now.ā Google analyst Thomas Monteiro at Investing Group said. āCompanies need to move really fast, even if that includes skipping a few steps along the way.ā
š©ŗ PULSE CHECK
Should companies prioritize speed or accuracy when developing AI tools?
AI RESEARCH
šByteDanceās G-DIG Method for Data Selection
Large Language Models (LLMs) are impressive general-purpose AI tools. However, they need fine-tuning with instructions to excel at specific tasks, like language translation.
The quality and variety of instructions used to fine-tune the LLM are crucial for its success. Poor or repetitive instructions wonāt lead to optimal language translation.
To solve this issue, ByteDance researchers developed G-DIG: a method that utilizes gradient-based techniques to select high-quality and diverse instruction data for LLMs.
G-DIG analyzes how instructions influence the LLM during the training process and identifies high-quality instructions that positively impact the AI modelās language translation performance.
G-DIG ensures a variety of influences by creating clusters of instructions based on how they affect the LLM and selecting a representative sample from each cluster.
š TRENDING TOOLS
šStacks is a search engine for your bookmarks.
šHamming launches trustworthy AI apps in weeks.
š·āāļøEververse builds your product roadmap at lightspeed.
šKerling is an in-context AI writing assistant for MacOS.
šµKudos is a free AI-powered wallet that automatically calculates credit card rewards.
š®Browse our always Up-To-Date AI Tools Database.
š°VENTURE CAPITAL UPDATES
š¼WHOāS HIRING?
VecFlow (San Francisco, CA): Full-Stack, Backend, ML Engineering Intern, Summer 2024
Tesla (Palo Alto, CA): Self-Driving AI Engineer Intern, Fall 2024
Nimble (Redwood City, CA): Software Engineer Intern, Fall 2024
Gatekeep (New York, NY): AI Software Engineer, Fashion App, New Grad
Waymo (Bellevue, WA): Software Engineer, Computer Vision/Deep Learning
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