PEARLS CONTEXTUAL BANDIT TUTORIAL
Pearls is an RL framework maintained by Meta. This tutorial walks through a bandit-based learning problem with the software.
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Pearls is an RL framework maintained by Meta. This tutorial walks through a bandit-based learning problem with the software.
The working paper "Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?" by researchers from MIT and IBM examines the economic viability of automating vision-based tasks. It found only 23% are cost-effective for automation. The paper predicts a gradual labor market impact over years, contrasting with more disruptive forecasts.
Nomic-Embed-Text-V1 sets a new standard as an open-source, fully reproducible text embedding model. It excels in both short and long-context tasks. Unique in its transparency, Nomic-Embed-Text-V1 offers complete access to its training code, model weights, and a vast dataset of 235 million text pairs.
Matrices is an AI-native spreadsheet that creates itself and fills itself with whatever information you need. It can be extended with just natural language.
BirdCast, a collaboration between the Cornell Lab of Ornithology, Colorado State University, and UMass Amherst, uses machine learning and radar data to predict bird migrations. The project demonstrates AI's potential to revolutionize ornithology by enhancing understanding of ecosystem health and migration patterns.
Roblox has developed an AI model capable of translating text chats in real-time across 16 languages to enhance user engagement by breaking down language barriers. It utilizes a transformer-based large language model within a Mixture-of-Experts architecture for efficient resource use while maintaining their privacy and safety processes.
The Japanese-based AI startup has been chosen to access the NEDO-funded supercomputer.
Hugging Face has introduced customizable Hugging Chat Assistants. This allows for the free creation of AI chatbots using a selection of open-source LLMs and contrasts with OpenAI's subscription-based model.
The Browser Company is developing AI technology for its Arc Browser to autonomously surf the web and present relevant information to users, unlike traditional search engines.
A fine-tuned BERT model is better than an off-the-shelf LLM like GPT-3.5-turbo at fake news detection.
PAP-REC has introduced a method to automatically create personalized prompts for Recommendation Language Models, enhancing their efficiency and effectiveness.
PAM is a tool that uses Audio-Language Models to assess audio quality without reference tracks or specialized training.
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Ramdas Naranyan, VP PM of Data Analytics and Insights Tech at Bank of America, joins Dave Mariani of AtScale [12]. They’ll discuss the various ways financial services firms use data to improve products, assess market opportunities, and select markets for expansion — as well as the role of AI [12] in personalization, and the need for
The Aphrodite engine can be used to reduce VRAM requirements while boosting throughput for AI inference workloads.
ChatLLM for VS Code is an open alternative for AI-assisted autocomplete. It now supports any Ollama models in addition to using closed API-based models.
Diffusers from Hugging Face has a number of interesting additions like video pipelines and multi-IP adapter usage, which allows conditioning on more than one image for generation.
Ollama recently released support for vision models. Llava 1.6 features updated support and includes vision functionality in both Python and JavaScript packages.
You can create a compelling image-to-music pipeline by translating images to text, text to prompt, and prompt to music.
AnimateLCM is a new approach for quickly creating high-quality videos and improving existing video diffusion models by splitting the learning process into two parts.
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Over 73% of companies are investing in AI and recruiting automation. This ebook covers the basic how-tos, ethical guidelines, and
Banana is winding down operations of its serverless GPU business. It has provided a transition plan and assistance for off-boarding.
Powerful text to 3D generative model that uses a two-stage process to generate candidates and then refine those chosen.
Get instant feedback on your sales emails.
OpenHermes-2.5 data has been used to train some of the best open models out there. The dataset contains 1M+ examples of high-quality data points. It has now been released.
Bard has now expanded its service to more languages and launched an image generation service.
a16z put together this list of 50 startups tackling some of America’s most pressing problems around defense, energy, transportation, and manufacturing. All of them are using AI in some form to accelerate their efforts. If you’re curious about real-world applications of AI, this is a great insight.
AI2 released a fully open language model training framework. The models come with comprehensive resources including full training data, model weights, training and evaluation code, over 500 checkpoints for each model, and future plans for fine-tuning code, all released under the Apache 2.0 License. These resources are provided by AI2’s Dolma and WIMBD. They include evaluation frameworks Catwalk and Paloma and support for analysis and fine-tuning through Weights & Biases logs and HuggingFace revisions. The models are competitive with the best in class.
Google has showcased a latent consistency diffusion model with some architectural changes that it trained to run on mobile devices with sub-second generation times.
Shared Network Pre-training (SNP) improves learning of video and text together. This method is more efficient and versatile than previous models and includes a unique strategy called Significant Semantic Strengthening (S3) for better understanding of key words in sentences.
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RAG is all the rage. Get insider tips on how to build more robust RAG in this upcoming virtual workshop [11]! Learn how to use Gretel’s Tabular LLM [11] to create diverse synthetic datasets for RAG evaluation. The session will be led by Sam Kemp, Principal AI Platform Architect at Microsoft, and the Gretel
The BGE-M3 project introduces a versatile embedding model that excels in Multi-Functionality (dense, multi-vector, and sparse retrieval), Multi-Linguality (supporting over 100 languages), and Multi-Granularity (handling inputs from short sentences to documents up to 8192 tokens). It uses a hybrid retrieval pipeline that combines different methods and re-ranking for higher accuracy and generalization, leveraging its ability to perform embedding and sparse retrieval simultaneously.
The Segment Anything Model (SAM) has been enhanced to create Hi-SAM, a model specializing in hierarchical text segmentation. Hi-SAM excels in segmenting text across multiple levels - from strokes to paragraphs - and even performs layout analysis.
RAGs is a Streamlit app that lets users create RAG pipelines from data sources using natural language. Users just have to describe the tasks and parameters they want from their RAG systems. The RAG can be queried and it will answer questions over the data.
IBM Consulting and Casper Labs are working together to build a pioneering AI governance tool powered by blockchain. Built leveraging IBM’s watsonx.governance platform, it will introduce AI version control, advanced monitoring, permissioning, and access controls to AI models for enterprise use. This could be essential for businesses looking to de-risk AI and harness its true potential while adhering to internal or external guidelines and regulations.
Just as the early days of the internet offered immense opportunities, today's AI landscape holds similar potential. The key is to shift perception to see the possibilities in existing technologies like AI and follow passion and joy to explore various paths.
Amazon has launched Rufus, an AI-powered shopping assistant in its mobile app that helps with product searches and recommendations by using Amazon's catalog and external web data, for a subset of U.S. customers.
6 agents that work together to build a newspaper by doing research, writing, and formatting in concert.
Find your potential clients' accurate contact data with AI.
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Building production-ready AI applications is hard and expensive. Anyscale [5] empowers builders to iterate fast with a simple user interface. Fine-tuning and deployment are 10x faster with automatic scaling and proactive resource management. You get the best cost-performance benefits using serverless or fully hosted on Ray. Ray is trusted by OpenAI, Uber, AWS, Spotify [5] and other AI leaders. Now, you can build your GenAI, conversational AI, or computer vision app easily — here’s how:
The AI community is abuzz with a leaked large language model called "miqu-1-70b" that was shared on HuggingFace and 4chan. The model shows performance rivaling OpenAI's GPT-4 and is linked to Mistral's Mixtral 8x7b. This incident, acknowledged by Mistral's CEO as a leak by an enthusiastic customer, highlights the growing capabilities of open source AI.
Dipendra Misra presented Layer-Selective Rank Reduction (LASER), a technique that improves large language model (LLM) accuracy by replacing a weight matrix with a smaller approximation, at the January Microsoft Research Forum.
The newest version of Llava, a vision language model, has improved OCR, reasoning, and world knowledge. It matches Gemini on some tasks. The Llava team plans to release data, code, and the model.
Weaver is a series of models specifically trained to tell stories. The largest model (34B params) outperforms GPT-4 on a storytelling benchmark.