#fastsearch — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #fastsearch, aggregated by home.social.
-
Muvera: Making multi-vector retrieval as fast as single-vector search
https://research.google/blog/muvera-making-multi-vector-retrieval-as-fast-as-single-vector-search/
#HackerNews #Muvera #MultiVector #Retrieval #FastSearch #AI #Research
-
Muvera: Making multi-vector retrieval as fast as single-vector search
https://research.google/blog/muvera-making-multi-vector-retrieval-as-fast-as-single-vector-search/
#HackerNews #Muvera #MultiVector #Retrieval #FastSearch #AI #Research
-
BM25 in PostgreSQL – 3x Faster Than Elasticsearch — https://blog.vectorchord.ai/vectorchord-bm25-revolutionize-postgresql-search-with-bm25-ranking-3x-faster-than-elasticsearch
#HackerNews #BM25 #PostgreSQL #Elasticsearch #FastSearch #DatabaseOptimization -
BM25 in PostgreSQL – 3x Faster Than Elasticsearch — https://blog.vectorchord.ai/vectorchord-bm25-revolutionize-postgresql-search-with-bm25-ranking-3x-faster-than-elasticsearch
#HackerNews #BM25 #PostgreSQL #Elasticsearch #FastSearch #DatabaseOptimization -
Introducing Phind-405B and faster, high quality #AI answers for everyone
🚀 Phind-405B: New flagship #llm, based on Meta Llama 3.1 405B, designed for programming & technical tasks. #Phind405B
⚡ 128K tokens, 32K context window at launch, 92% on HumanEval, great for web app design. #Programming #AIModel
💡 Trained on 256 H100 GPUs with FP8 mixed precision, 40% memory reduction. #DeepSpeed #FP8
⚡ Phind Instant Model: Super fast, 350 tokens/sec, based on Meta Llama 3.1 8B. #PhindInstant
🚀 Runs on NVIDIA TensorRT-LLM with flash decoding, fused CUDA kernels. #NVIDIA #GPUs
🔍 Faster Search: Prefetches results, saves up to 800ms latency, better embeddings. #FastSearch
👨💻 Goal: Help developers experiment faster, new features coming soon! #DevTools #Innovation
https://www.phind.com/blog/introducing-phind-405b-and-better-faster-searches
-
Introducing Phind-405B and faster, high quality #AI answers for everyone
🚀 Phind-405B: New flagship #llm, based on Meta Llama 3.1 405B, designed for programming & technical tasks. #Phind405B
⚡ 128K tokens, 32K context window at launch, 92% on HumanEval, great for web app design. #Programming #AIModel
💡 Trained on 256 H100 GPUs with FP8 mixed precision, 40% memory reduction. #DeepSpeed #FP8
⚡ Phind Instant Model: Super fast, 350 tokens/sec, based on Meta Llama 3.1 8B. #PhindInstant
🚀 Runs on NVIDIA TensorRT-LLM with flash decoding, fused CUDA kernels. #NVIDIA #GPUs
🔍 Faster Search: Prefetches results, saves up to 800ms latency, better embeddings. #FastSearch
👨💻 Goal: Help developers experiment faster, new features coming soon! #DevTools #Innovation
https://www.phind.com/blog/introducing-phind-405b-and-better-faster-searches
-
Introducing Phind-405B and faster, high quality #AI answers for everyone
🚀 Phind-405B: New flagship #llm, based on Meta Llama 3.1 405B, designed for programming & technical tasks. #Phind405B
⚡ 128K tokens, 32K context window at launch, 92% on HumanEval, great for web app design. #Programming #AIModel
💡 Trained on 256 H100 GPUs with FP8 mixed precision, 40% memory reduction. #DeepSpeed #FP8
⚡ Phind Instant Model: Super fast, 350 tokens/sec, based on Meta Llama 3.1 8B. #PhindInstant
🚀 Runs on NVIDIA TensorRT-LLM with flash decoding, fused CUDA kernels. #NVIDIA #GPUs
🔍 Faster Search: Prefetches results, saves up to 800ms latency, better embeddings. #FastSearch
👨💻 Goal: Help developers experiment faster, new features coming soon! #DevTools #Innovation
https://www.phind.com/blog/introducing-phind-405b-and-better-faster-searches
-
Introducing Phind-405B and faster, high quality #AI answers for everyone
🚀 Phind-405B: New flagship #llm, based on Meta Llama 3.1 405B, designed for programming & technical tasks. #Phind405B
⚡ 128K tokens, 32K context window at launch, 92% on HumanEval, great for web app design. #Programming #AIModel
💡 Trained on 256 H100 GPUs with FP8 mixed precision, 40% memory reduction. #DeepSpeed #FP8
⚡ Phind Instant Model: Super fast, 350 tokens/sec, based on Meta Llama 3.1 8B. #PhindInstant
🚀 Runs on NVIDIA TensorRT-LLM with flash decoding, fused CUDA kernels. #NVIDIA #GPUs
🔍 Faster Search: Prefetches results, saves up to 800ms latency, better embeddings. #FastSearch
👨💻 Goal: Help developers experiment faster, new features coming soon! #DevTools #Innovation
https://www.phind.com/blog/introducing-phind-405b-and-better-faster-searches
-
Introducing Phind-405B and faster, high quality #AI answers for everyone
🚀 Phind-405B: New flagship #llm, based on Meta Llama 3.1 405B, designed for programming & technical tasks. #Phind405B
⚡ 128K tokens, 32K context window at launch, 92% on HumanEval, great for web app design. #Programming #AIModel
💡 Trained on 256 H100 GPUs with FP8 mixed precision, 40% memory reduction. #DeepSpeed #FP8
⚡ Phind Instant Model: Super fast, 350 tokens/sec, based on Meta Llama 3.1 8B. #PhindInstant
🚀 Runs on NVIDIA TensorRT-LLM with flash decoding, fused CUDA kernels. #NVIDIA #GPUs
🔍 Faster Search: Prefetches results, saves up to 800ms latency, better embeddings. #FastSearch
👨💻 Goal: Help developers experiment faster, new features coming soon! #DevTools #Innovation
https://www.phind.com/blog/introducing-phind-405b-and-better-faster-searches