ContentPosts from @kala..
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@kala shared a link, 2 days, 4 hours ago
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I Measured Claude 4.7's New Tokenizer. Here's What It Costs You.

Anthropic's Claude Opus 4.7 migration guide states the new tokenizer utilizes "roughly 1.0 to 1.35x as many tokens" compared to 4.6. Actual measurements show a higher ratio on technical docs and real CLAUDE.md files. The cost of the new tokenizer was measured using real content and synthetic samples.. read more  

I Measured Claude 4.7's New Tokenizer. Here's What It Costs You.
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@kala shared a link, 2 days, 4 hours ago
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Anthropic releases Claude Opus 4.7, narrowly retaking lead for most powerful generally available LLM

Anthropic has unveiled Claude Opus 4.7, a powerful large language model that outperforms key rivals like GPT-5.4 and Google's Gemini 3.1 Pro in benchmarks such as agentic coding and financial analysis. Opus 4.7 leads the market on the GDPVal-AA knowledge work evaluation with an Elo score of 1753 and.. read more  

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@kala shared a link, 2 days, 4 hours ago
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Critical Claude Code vulnerability: Deny rules silently bypassed because security checks cost too many tokens

Clause Code security bypass: Anthropic's performance fix silently disabled deny rules for 500K+ developers when more than 50 subcommands were used in a command, impacting permission validation and security policy enforcement. The vulnerability stemmed from a tradeoff between security and performance.. read more  

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@kala shared a link, 2 days, 4 hours ago
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Scaling MCP adoption: Our reference architecture for simpler, safer and cheaper enterprise deployments of MCP

Cloudflare centralized MCP servers in a monorepo. It added governed templates, Cloudflare Access auth, audit logs, and DLP behind an MCP server portal. It launched Code Mode to collapse many tool schemas into two portal tools. Token use fell ~94%. Cloudflare Gateway now finds shadow MCP servers... read more  

Scaling MCP adoption: Our reference architecture for simpler, safer and cheaper enterprise deployments of MCP
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@kala shared a link, 2 days, 4 hours ago
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China has ‘nearly erased’ America’s lead in AI

Stanford HAI's 2026 AI Index shows China cut the U.S. lead inArenascores. In March 2026,Claude Opus 4.6ledDola‑Seed 2.0by 2.7%. A 2.7% margin is a photo finish. China outpaces the U.S. inpublicationcitations (20.6% vs 12.6% in 2024) and inindustrial robots(~295,000 vs 34,200). It also holds surplusc.. read more  

China has ‘nearly erased’ America’s lead in AI
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@kala shared a link, 2 weeks, 3 days ago
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Why we're rethinking cache for the AI era

Cloudflare data shows that 32% of network traffic originates from automated traffic, including AI assistants fetching data for responses. AI bots often issue high-volume requests and access rarely visited content, impacting cache efficiency. Cloudflare researchers propose AI-aware caching algorithms.. read more  

Why we're rethinking cache for the AI era
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@kala shared a link, 2 weeks, 3 days ago
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State of Context Engineering in 2026

Context engineering has evolved in the AI engineering field since mid-2025 with the introduction of patterns for managing context effectively. These patterns include progressive disclosure, compression, routing, retrieval strategies, and tool management, each addressing a different dimension of the .. read more  

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@kala shared a link, 2 weeks, 3 days ago
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Qwen3.6-Plus: Towards Real World Agents

Qwen3.6-Plus, the latest release following Qwen3.5 series, offers enhanced agentic coding capabilities and sharper multimodal reasoning. The model excels in frontend web development and complex problem-solving, setting a new standard in the developer ecosystem. Qwen3.6-Plus is available via Alibaba .. read more  

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@kala shared a link, 2 weeks, 3 days ago
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Our most intelligent open models, built from Gemini 3 research and technology to maximize intelligence-per-parameter

Built from Gemini 3 research and technology, Gemma 4 offers maximum compute and memory efficiency for mobile and IoT devices. Develop autonomous agents, multimodal applications, and multilingual experiences with Gemma 4's unprecedented intelligence-per-parameter... read more  

Our most intelligent open models, built from Gemini 3 research and technology to maximize intelligence-per-parameter
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@kala shared a link, 2 weeks, 3 days ago
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From zero to a RAG system: successes and failures

An engineer spun up an internal chat with a localLLaMAmodel viaOllama, a PythonFlaskAPI, and aStreamlitfrontend. They moved off in-memoryLlamaIndexto batch ingestion intoChromaDB(SQLite). Checkpoints and tolerant parsing went in to stop RAM disasters. Indexing produced 738,470 vectors (~54 GB). They.. read more  

From zero to a RAG system: successes and failures