Results for “context engineering”

…Claude 2.1 well it recalls information across its 200,000 token context window. However, @if_a also considers that testing the long context capability will require more work on prompt engineering. Evaluating AI Models: @gabriel_syme…

…datasets to developing Elaborator models using prompt engineering. Unsloth AI discussion 3. Multimodal AI and Emerging Architectures Anticipation surrounds the integration of ChatGPT voice conversational AI with Open Interpreter API,…

…abilities, a wider coverage of languages and longer context – at least 128K tokens A new function calling guide for GoogleDeepMind Gemini, using the new uSDKs, has been announced by @_philschmid, and includes multiple full examples for…

…claim: instead of keeping everything in an expensive active context window, you can compile task descriptions or long documents into adapter weights with sub-second latency, enabling rapid adaptation and “durable memory”-like behavior…

…reported, comparisons to DeepSeek V3 and GPT-4o couldnt really contextualize Command A among either SOTA open source or overall SOTA-for-size), it was hard to tell where it would rank in terms of lasting impact. With today's LMArena result,…

…simplicity in development and deployment, particularly in the context of AI model hosting and managing dependencies. Theme 4. Gemma 3, Mistral 24B, and QwQ 32B: Performance Comparison Gemma 3 27b vs. Mistral 24b vs. QwQ 32b: I tested on…

…and exploration. Theme 3. Granite 3.1 Language Models: 128k Context & Open License Granite 3.1 Language Models: 128k context length & Apache 2.0 (Score: 144, Comments: 22): Granite 3.1 Language Models now feature a 128k context length and…

…Memories, Development Challenges with Cascade, Prompt Engineering and Context, AI Integration in Programming, User Experiences with Windsurf Windsurf's Auto-Generated Memories Feature: Users expressed excitement about Windsurf's…

…and updated pricing information to improve user experience. AI Context Understanding Issues Reported: Users have encountered errors like 'The code edit failed to apply' and 'Cascade has encountered an internal error', especially when using …

…reasoning tasks. The post did not provide further details or context about the model's capabilities or applications. Many users express skepticism about Phi models, stating they perform well on benchmarks but fall short in real-world…

…transformer models on benchmarks. These models boast a 32k context window and minimal memory footprint, handling 1M tokens efficiently. @perplexity_ai teased an upcoming feature with "⌘ + ⇧ + P — coming soon," hinting at new functionalities…

…Agent, and @0xSero compressing Qwen3.5-35B enough to fit full context into 24GB VRAM at roughly 1% average performance drop. Quantization and cache work remain key enablers: @iotcoi shipped a TurboQuant vLLM fork with fused Triton KV write …