Programming AI is fundamentally similar to a compiler, with English being a poor input language choice due to its imprecision and non-deterministic nature. While AI tools can enhance programming workflows through improved search and pattern recognition, the current hype around AI coding overlooks its limitations and the need for better programming languages and tools.
https://geohot.github.io//blog/jekyll/update/2025/09/12/ai-coding.html
#aidevelopment #programming #techhype #softwaretools #industrycritique
Programming AI is fundamentally similar to a compiler, with English being a poor input language choice due to its imprecision and non-deterministic nature. While AI tools can enhance programming workflows through improved search and pattern recognition, the current hype around AI coding overlooks its limitations and the need for better programming languages and tools.
https://geohot.github.io//blog/jekyll/update/2025/09/12/ai-coding.html
#aidevelopment #programming #techhype #softwaretools #industrycritique
Programming AI is fundamentally similar to a compiler, with English being a poor input language choice due to its imprecision and non-deterministic nature. While AI tools can enhance programming workflows through improved search and pattern recognition, the current hype around AI coding overlooks its limitations and the need for better programming languages and tools.
https://geohot.github.io//blog/jekyll/update/2025/09/12/ai-coding.html
#aidevelopment #programming #techhype #softwaretools #industrycritique
Programming AI is fundamentally similar to a compiler, with English being a poor input language choice due to its imprecision and non-deterministic nature. While AI tools can enhance programming workflows through improved search and pattern recognition, the current hype around AI coding overlooks its limitations and the need for better programming languages and tools.
https://geohot.github.io//blog/jekyll/update/2025/09/12/ai-coding.html
#aidevelopment #programming #techhype #softwaretools #industrycritique
Programming AI is fundamentally similar to a compiler, with English being a poor input language choice due to its imprecision and non-deterministic nature. While AI tools can enhance programming workflows through improved search and pattern recognition, the current hype around AI coding overlooks its limitations and the need for better programming languages and tools.
https://geohot.github.io//blog/jekyll/update/2025/09/12/ai-coding.html
#aidevelopment #programming #techhype #softwaretools #industrycritique
Programming AI is fundamentally similar to a compiler, with English being a poor input language choice due to its imprecision and non-deterministic nature. While AI tools can enhance programming workflows through improved search and pattern recognition, the current hype around AI coding overlooks its limitations and the need for better programming languages and tools.
https://geohot.github.io//blog/jekyll/update/2025/09/12/ai-coding.html
#aidevelopment #programming #techhype #softwaretools #industrycritique
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Google Research introduces VaultGemma, a 1B-parameter language model trained with differential privacy, establishing new scaling laws for privacy-utility trade-offs in AI development. The model demonstrates strong privacy protections while maintaining utility comparable to non-private models from 5 years ago, marking a significant advancement in private AI development.
https://research.google/blog/vaultgemma-the-worlds-most-capable-differentially-private-llm/
#aiprivacy #machinelearning #differentialprivacy #languagemodels #googleresearch
Vectroid introduces a serverless vector search solution that maintains high accuracy and low latency while being cost-effective. The platform leverages HNSW algorithm with optimized resource allocation and dynamic scaling capabilities, delivering over 90% recall while handling high query loads. It operates through independently scalable microservices for reads and writes, with data persisted to cloud object storage.
https://www.vectroid.com/blog/why-and-how-we-built-Vectroid
#vectorsearch #serverless #hnsw #performance #scalability
Vectroid introduces a serverless vector search solution that maintains high accuracy and low latency while being cost-effective. The platform leverages HNSW algorithm with optimized resource allocation and dynamic scaling capabilities, delivering over 90% recall while handling high query loads. It operates through independently scalable microservices for reads and writes, with data persisted to cloud object storage.
https://www.vectroid.com/blog/why-and-how-we-built-Vectroid
#vectorsearch #serverless #hnsw #performance #scalability
Vectroid introduces a serverless vector search solution that maintains high accuracy and low latency while being cost-effective. The platform leverages HNSW algorithm with optimized resource allocation and dynamic scaling capabilities, delivering over 90% recall while handling high query loads. It operates through independently scalable microservices for reads and writes, with data persisted to cloud object storage.
https://www.vectroid.com/blog/why-and-how-we-built-Vectroid
#vectorsearch #serverless #hnsw #performance #scalability
Vectroid introduces a serverless vector search solution that maintains high accuracy and low latency while being cost-effective. The platform leverages HNSW algorithm with optimized resource allocation and dynamic scaling capabilities, delivering over 90% recall while handling high query loads. It operates through independently scalable microservices for reads and writes, with data persisted to cloud object storage.
https://www.vectroid.com/blog/why-and-how-we-built-Vectroid
#vectorsearch #serverless #hnsw #performance #scalability
Vectroid introduces a serverless vector search solution that maintains high accuracy and low latency while being cost-effective. The platform leverages HNSW algorithm with optimized resource allocation and dynamic scaling capabilities, delivering over 90% recall while handling high query loads. It operates through independently scalable microservices for reads and writes, with data persisted to cloud object storage.
https://www.vectroid.com/blog/why-and-how-we-built-Vectroid
#vectorsearch #serverless #hnsw #performance #scalability