⚡️ Fully Open-Source LLM

Good Morning. The field of AI witnesses a groundbreaking move with LLM360, touted to be the first fully open-source and transparent LLM initiative. Let’s dive in.

Today’s Highlights:

• OpenAI Startup Fund launches Converge 2

• Google introduces AI music composer, MusicFX

• Australian scientists to unveil brain-mimicking supercomputer

DEEP DIVE

LLM360 Initiative Unveils Fully Open-Source LLMs

The AI research community is no stranger to open-source projects, but full transparency has often been one step too far. That changes with LLM360—a groundbreaking initiative dedicated to making the entire process of LLM training open to all.

Unlike previous LLMs where accessibility was partial, LLM360 promises an end-to-end mapping of LLM pre-training paths. This open-source model grants scholars and AI enthusiasts the tools needed to understand, replicate, and innovate upon existing LLM training methods.

But what's in the box?

• LLM360 features two 7B parameter models, AMBER and CRYSTALCODER.

• It includes extensive resources—training codes, full datasets, intermediate checkpoints, and detailed analyses of each pre-training step.

It's about trust and progress: By revealing the pre-training dataset specifics and operational intricacies, LLM360 eradicates the guesswork from model training. This transparency is crucial to evaluate LLMs' risks and replicate them faithfully, potentially reducing duplicated effort in the research community.

Interestingly, benchmark tests on datasets like ARC and HellaSwag show these models' promise, particularly after fine-tuning, while shedding light on areas needing improvement.

Though this level of openness is rare, it's not unprecedented—projects like Pythia, EleutherAI's GPT-J, and GPT-NeoX have laid the groundwork in this area. LLM360 takes it a leap further, supporting researchers in dissecting and finding correspondence between metrics, data chunks, and checkpoints efficiently.

The era of concealed code and obscured datasets is being challenged. LLM360 reflects a commitment to communal growth and the shared pursuit of AI mastery.

Keep reading here.

PUNCHLINES

Glean Machine: Startup founded by ex-Google search team, Glean, nears $2B valuation.

AI's Got Talent: OpenAI Startup Fund launches second Converge startup cohort.

Ears to AI: MIT's study tunes into AI that echoes human hearing ability—aiming to revolutionize hearing aids.

Coding Sidekicks: Google's Duet AI for developers steps out of beta, promising to harmonize with coders' keystrokes.

Byline by AI: OpenAI joins Rolling Stone publisher to merge AI with journalism.

TLDR

Midjourney Alpha launches for prolific creators: Midjourney's new alpha web platform now caters to power users who've created over 10,000 images, offering a streamlined, minimalist interface for AI-driven image generation. The web version contrasts with Discord's bot commands, featuring an "Explore" section for public viewing and upcoming plans for an iOS app and organizational folders.

Google introduces AI music composer, MusicFX: Google's MusicFX, an AI-based music creation tool, empowers users to produce unique tracks from simple text prompts. Featuring MusicLM and SynthID for watermarking, MusicFX prioritizes ethical AI by limiting generation that mimics specific artists or vocals.

DeepMind's Imagen 2 elevates AI imagery: Google's DeepMind reveals Imagen 2, which uses diffusion technology for top-notch, realistic images matching users' prompts with improved accuracy. It boasts new features like inpainting/outpainting, refined with human aesthetic preferences, and sets the stage for potential video AI advancements, though it's not ready for public use pending further safety measures.

Australian scientists to unveil brain-mimicking supercomputer: Western Sydney University researchers gear up to launch DeepSouth in 2024. This neuromorphic supercomputer can perform 228 trillion synaptic operations per second, mirroring human brain capabilities, and will propel advancements in AI, robotics, and smart devices.

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