AI2 Incubator

Have you ever struggled with how to segment/chunk in your RAG applications? Harmonious' spotlight paper this past week dives into this problem, providing a few ideas. Benchmarking continues to be the center of attention. Other LLM-related topics include knowledge editing, introspection, math reasoning, cognitive behavior therapy, design-to-html, and web agents. Finally, there's a paper describing AutoTrain, an open-source library authored by the world's first Kaggle Quadruple Grandmaster. https://lnkd.in/gHC8JkZZ #ai2incubator #harmonious

📌 This week we have two spotlight papers at Harmonious.ai, one of which is a massive technical report from perhaps the most formidable AI big tech company today, claiming SOTA performances beating everyone from OpenAI's Sora to hot startups such as Runway, Luma, Pika, and Eleven Labs. 📌 The number one research topic at the moment is hands down benchmarking and evaluation (2 out of 3 among the papers I reviewed this week). 📌 OpenAI's o1 models absolutely dominate in one of the benchmarks (JudgeBench). 📌 There's the introduction of the first true multimodal, open-weight model from one of China's AI Tigers. 📌 A new concept to watch is Flow Matching which was introduced just under two years ago. 📌 What's cooler than LLM-as-a-Judge? It's Agent-as-a-Judge! 📌 What's cooler than RAG? A RAG that can see: VisRAG! Read more at https://lnkd.in/gQpA_tvA Every week I read about 100 papers shared by the fine folks at Hugging Face, provide short commentaries for a couple of dozens, and select one or two as spotlights. Sign up at https://harmonious.ai to get the scoop delivered weekly to your mailbox. #ai2incubator #harmonious

Are you building RAG and interested in inference time scaling (o1 etc?). Then Harmonious' spotlight paper from Google DeepMind is your must read. Another interesting paper I read is from a duo of MIT alums and seemingly co-founders of an obscure startup called BitEnergy, with jaw dropping claims of making transformers 5X to 20X more energy efficient (it was even covered by Yahoo!). Don't want to miss my weekly AI paper roundups? Take 10 seconds to sign up at https://harmonious.ai and have them delivered to your mailbox! https://lnkd.in/gV6UC9za #ai2incubator #harmonious

How do startups building GenAI/LLM-based products interview candidates for data scientist, AI engineer, and applied researcher roles? My quick googling showed guides suggesting questions about SQL, Spark, PyTorch, gradient boosting, L1 vs L2 penalty, etc. I believe that those skills may be relevant pre-ChatGPT, but increasingly insufficient in today's world of RAG, GenAI UX, agents, prompt management, AI API orchestration, guard rails, etc. Founders, please share your experiences/perspectives. I'll share mine in an upcoming post. PC: Dalle3 via ChatGPT.

Harmonious' weekly paper roundup: 📌 Spotlight paper is from Meta's Llama team, its title is inspired by a game show 📌 Multimodality is still very active, with speech and video making progress 📌 AI-generated synthetic data is pervasive 📌 GPTs still have the upper hands on new (hence lesser-known) benchmarks. OpenAI is still the best in the business in avoiding overfitting 📌 ByteDance may have come up with a nice improvement on residual connection: hyper connection. Resnet 👉 HyperNet? 📌 The frightening pace of AI research from Chinese institutions continues 📌 Apple is publishing a lot more Read more at: https://lnkd.in/dxPbYD7M #ai2incubator #harmonious

At the beginning of this year, I wrote in Insight #13: """ 2024 Prediction: VoiceGPTs We wrap up Insight #13 with our prediction for 2024. Similar to many other 2024 predictions, we anticipate multimodal models to take center stage. We are particularly excited about models that combine text and speech modalities, enabling seamless end-to-end conversations that are voice-based. This is in contrast to the current pipelined approach of sandwiching an LLM with a pair of speech-to-text and text-to-speech models that results in highly stilted, walkie-talkie-like experience. Multimodal text and speech models, which we refer to as VoiceGPTs, will elevate the popular ChatGPT experience beyond the confines of the keyboard. Imagine having a natural conversation about any topic with a VoiceGPT on your Alexa, Siri, or Home device. This is a highly non-trivial technical challenge. We will only see a preview of such technology in 2024. """ Fast forward 9 months, I was proven to be a bit too cautious. First, OpenAI announced in May GPT-4o, with scifi-like demos evocative of the movie Her (and drawing the ire of Scarlett Johansson). GPT-4o's voice mode was rolled out to users earlier this month. OpenAI continues to show the way, leaving the rest of the industry (Anthropic, Google, Meta, etc.) scrambling to catch up. The company that is closest to catching up here is however a French AI research lab "with a $330 million budget that will make everything open source". It is called Kyutai. Last week they shared Moshi (model, weights for Moshi and its Mimi codec, streaming inference code in Pytorch, Rust and MLX, and a fantastic technical report). Amazing! Moshi's technical report is our pick for past week's spotlight paper at Harmonious. https://lnkd.in/gFEVEdTq #ai2incubator #harmonious

Harmonious' spotlight paper this week: OLMoE: Open Mixture-of-Experts Language Models Authors: Allen Institute for AI; Contextual AI; University of Washington; Princeton University    This paper presents OLMoE, an innovative language model leveraging a sparse Mixture-of-Experts architecture, which achieves remarkable efficiency and performance with its 7 billion parameters. I found the emphasis on key design choices and their detailed analysis of MoE training particularly insightful. The open-source nature of their work fosters transparency and collaboration in the AI community. However, the high computational resources required for pretraining may limit accessibility for many academic institutions. Lastly, I am curious about whether the outcomes observed in smaller models will hold true in significantly larger models. #harmoniou #ai2incubator

Harmonious' weekly paper roundup for the week of August 26, 2024. The reviewed papers collectively delve into various advancements in AI models, particularly focusing on multimodal, vision-language, and inference strategies. Several papers explore the enhancement of Large Language Models (LLMs) through innovative techniques such as improved inference patterns for long contexts, the utilization of mixed encoders, and energy-efficient on-device processing (WiM, Eagle, Dolphin). Another recurring theme is multimodality, with in-depth studies on optimizing LLMs for cross-modal alignment and real-time interactions in complex environments (Law of Vision Representation, GameNGen, CogVLM2). Further contributions include advancements in text-to-image diffusion models, audio language modeling, and AI-generated content in music, reflecting the expanding scope of AI applications (SwiftBrush v2, WavTokenizer, Foundation Models for Music). The practical impact of these models is underscored by initiatives to enhance the functionality and accessibility of benchmarks and operational pipelines, ensuring robust performance in real-world scenarios (SWE-bench-java, LlamaDuo, MME-RealWorld). https://lnkd.in/gw7za8-X #ai2incubator #harmonious

About 3 years ago (Fall 2021) I wrote about LLMs and mused about the concept of task-centric AI as an emerging addition to Andrew Ng's initiative on data-centric AI: "What's with the brouhaha around LLMs? Learning efficiency! Below is the famous GPT-3 graph that got everyone's attention ... Instead of building 10 models with 1,000 labels per, we could build 1,000 models with 10 labels per ... In the task-centric world, LLMs could open up the opportunity to help less technical folks build and use AI models without relying on an expensive data science team. No-code AI, powered by the XXL transformers near you? Scale.ai and Snorkel.ai are the poster-child unicorns of the data-centric AI world. Who will emerge as the representatives for the LLM task-centric world?" While the term task-centric AI did not catch on—GenAI is the chosen one (I am neither Andrew Ng nor marketing expert), it essentially describes the AI world we have today. Is there something as transformative lurking on the horizon? I have not seen anything like it following recent AI research (and occasionally sharing thoughts on harmonious.ai). There will be one for sure, and let's be on the lookout. https://lnkd.in/gtQcm-cJ PS: The Yoodli team is on a tear. Go Esha Joshi & Varun Puri! #ai2incubator #startup #llm #genai #task_centric_AI