InfoQ Homepage Large language models Content on InfoQ
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Microsoft's Orca 2 LLM Outperforms Models That Are 10x Larger
Microsoft Research released its Orca 2 LLM, a fine-tuned version of Llama 2 that performs as well as or better than models that contain 10x the number of parameters. Orca 2 uses a synthetic training dataset and a new technique called Prompt Erasure to achieve this performance.
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Anthropic Announces Claude 2.1 LLM with Wider Context Window and Support for AI Tools
According to Anthropic, the newest version of Claude delivers many “advancements in key capabilities for enterprises—including an industry-leading 200K token context window, significant reductions in rates of model hallucination, system prompts and our new beta feature: tool use.” Anthropic also announced reduced pricing to improve cost efficiency for our customers across models.
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xAI Introduces Large Language Model Grok
xAI, the AI company founded by Elon Musk, recently announced Grok, a large language model. Grok can access current knowledge of the world via the X platform and outperforms other LLMs of comparable size, including GPT-3.5, on several benchmarks.
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AI Researchers Improve LLM-Based Reasoning by Mimicking Learning from Mistakes
Researchers from Microsoft, Peking University, and Xi’an Jiaotong University claim to have developed a technique to improve large language models' (LLMs) ability to solve math problems by replicating how humans learn from their own mistakes.
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Jina AI's Open-Source Embedding Model Outperforms OpenAI's Ada
Multimodal AI company Jina AI recently released jina-embeddings-v2, a sentence embedding model. The model supports context lengths up to 8192 tokens and outperforms OpenAI's text-embedding-ada-002 on several embedding benchmarks.
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Google Open-Sources AI Fine-Tuning Method Distilling Step-by-Step
A team from the University of Washington and Google Research recently open-sourced Distilling Step-by-Step, a technique for fine-tuning smaller language models. Distilling Step-by-Step requires less training data than standard fine-tuning and results in smaller models that can outperform few-shot prompted large language models (LLMs) that have 700x the parameters.
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Google DeepMind Announces LLM-Based Robot Controller RT-2
Google DeepMind recently announced Robotics Transformer 2 (RT-2), a vision-language-action (VLA) AI model for controlling robots. RT-2 uses a fine-tuned LLM to output motion control commands. It can perform tasks not explicitly included in its training data and improves on baseline models by up to 3x on emergent skill evaluations.
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Defensible Moats: Unlocking Enterprise Value with Large Language Models at QCon San Francisco
In a recent presentation at QConSFrancisco, Nischal HP discussed the challenges enterprises face when building LLM-powered applications using APIs alone. These challenges include data fragmentation, the absence of a shared business vocabulary, privacy concerns regarding data, and diverse objectives among stakeholders.
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The Challenges of Producing Quality Code When Using AI-Based Generalistic Models
Using AI with generalistic models to do very specific things like generating code can cause problems. Producing code with AI is like using code from someone else who you don’t know which may not match your standards and quality. Creating specialised or dedicated models can be a way out.
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Practical Advice for Retrieval Augmented Generation (RAG), by Sam Partee at QCon San Francisco
At the recent QCon San Francisco conference, Sam Partee, principal engineer at Redis, gave a talk about Retrieval Augmented Generation (RAG). He discussed Generative Search, which combines large language models (LLMs) with vector databases to improve information retrieval. Partee discussed several innovative tricks such as Hypothetical Document Embeddings (HyDE), and semantic caching.
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Generative AI Service AWS Bedrock Now Generally Available
After announcing Bedrock last April in preview, Amazon is now making its fully-managed service for generative AI apps generally available.
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Multi-Modal LLM NExT-GPT Handles Text, Images, Videos, and Audio
The NExT Research Center at the National University of Singapore (NUS) recently open-sourced NExT-GPT, an "any-to-any" multi-modal large language model (LLM) that can handle text, images, videos, and audio as input or output. NExT-GPT is based on existing pre-trained models and only required updating 1% of its total parameters during training.
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Hugging Face's Guide to Optimizing LLMs in Production
When it comes to deploying Large Language Models (LLMs) in production, the two major challenges originate from the huge amount of parameters they require and the necessity of handling very long input sequences to represent contextual information. Hugging Face has documented a list of techniques to tackle those hurdles based on their experience serving such models.
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Abu Dhabi Releases Largest Openly-Available Language Model Falcon 180B
The Abu Dhabi government's Technology Innovation Institute (TII) released Falcon 180B, currently the largest openly-available large language model (LLM). Falcon 180B contains 180 billion parameters and outperforms GPT-3.5 on the MMLU benchmark.
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AI, ML, Data Engineering News Roundup: Stable Chat, Vertex AI, ChatGPT and Code Llama
The most recent update, which covers developments through September 4, 2023, highlights significant pronouncements and accomplishments in the fields of artificial intelligence, machine learning, and data science. Developments from Stability AI, Google, OpenAI, and Meta were among this week's significant stories.