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Apple overtook Nvidia on Friday to become the world’s most valuable company, reshuffling the top ranks of tech heavyweights as investors reassess the outlook for artificial intelligence. Apple's market cap stood at $4.88tn while Nvidia fell to $4.86tn after a 3.5% decline.

Lowest cost per token from extreme codesign maximizes intelligence per dollar for post-training in the agentic era.

NVIDIA released Nemotron 3 Embed on July 15 and 16, 2026. The collection has three open checkpoints: Nemotron-3-Embed-8B-BF16, Nemotron-3-Embed-1B-BF16, and Nemotron-3-Embed-1B-NVFP4. The 8B ranks #1 on RTEB at 78.46 average NDCG@10. The 1B came from ModelOpt NAS pruning plus COS+MSE distillation from the 8B teacher. NVFP4 retains 99%+ of BF16 retrieval accuracy at up to 2x Blackwell throughput. All three run 32,768-token inputs under OpenMDW-1.1.

Chinese chip designers Moore Threads and Hygon project strong revenue growth driven by surging domestic AI demand. Moore Threads expects 135-149% revenue increase, while Hygon forecasts 55.6-70.2% growth. This highlights China's push for domestic AI chips amid US export restrictions.

Warren Buffett disclosed that he personally initiated Berkshire Hathaway's $31 billion investment in Alphabet, Google's parent company. He explained that the capital expenditure model of AI giants now resembles that of railroads and utilities, which he understands well, convincing him to overcome his long-standing aversion to tech stocks.

Proposes Branching Policy Optimization (BPO), which leverages deterministic, snapshottable, and resumable sandboxes to construct a tree-structured rollout topology with shared prefixes, reducing policy gradient variance and improving success rates by 3.6–6.1 absolute points over GRPO and RLOO.

As enterprises race to scale AI, the biggest obstacle to performance and ROI may be the infrastructure moving data, not the hardware processing it. The article argues that idle GPUs are often due to 'data starvation' caused by inefficient storage-to-compute data pipelines. It advocates for a loosely coupled architecture with an application delivery controller to optimize data flow, and highlights three dimensions of resilience: reachability, policy, and delivery.

Moonshot AI released Kimi K3, a 2.8T-parameter open-weight model with 1M context, achieving top rankings in Frontend Code Arena and competitive scores in various benchmarks. The release marks a milestone for open models, though some gaps remain versus top closed models. The newsletter also covers other AI news including safety incidents, agent frameworks, and robotics.

SAM is a free, open-source AI agent that runs locally on your computer, no subscription needed. It goes beyond chat to actually execute tasks, with 173 tools, team collaboration, offline capability, and privacy by design.

Moonshot AI released Kimi K3 on July 16, 2026, a 2.8-trillion-parameter open MoE model with native vision, 1M context window, and innovations like Kimi Delta Attention and Attention Residuals. It outperforms many open models but trails top proprietary models on certain benchmarks.

AegisDB is a self-hosted memory system for AI agents, offering durable episodic, semantic (vector search), and volatile working memory through a simple JSON-over-TCP protocol. It is a single dependency-free C binary with multi-tenancy, encryption, backups, read replicas, and a one-command Prometheus/Grafana observability stack. Designed for privacy, it ensures your agents' memory stays on your infrastructure with no SaaS dependencies.

Artificial Analysis released AA-Briefcase agentic knowledge work benchmark results; Kimi K3 scores 1547 Elo, ranking first, surpassing GPT-5.6 Sol's 1495. The benchmark simulates real business workflows evaluating models on spreadsheets, presentations, memos, etc.

Cushman & Wakefield’s Chief Digital and Information Officer Sal Companieh discusses building an enterprise AI core through a product operating model, unified data strategy, and partnership with Databricks, reducing idea-to-outcome timelines from months to days.

Skyportal SRE is an open-source AI infrastructure engineer tool providing a Python SDK, CLI, and observability agent for managing and monitoring AI infrastructure.

We improved the LeRobot video reader in Daft by batching decodes, reducing frame decode time on remote datasets from ~3s per frame to seconds in total, achieving 4-15x speedups.

The startup, backed by Nvidia and Boeing, said its wheeled robots are already working in production and can continuously learn new industrial tasks.

Anthropic secretly degraded its most powerful coding agent, Claude Fable 5, to limit its effectiveness on frontier AI development tasks, revealing a structural contradiction: labs must break their own products to protect their position. Meanwhile, open-weight models are closing the gap and enterprise customers are fleeing to cheaper alternatives.

Energy companies raised $12.6 billion via IPOs in H1 2026, the highest half-year level since the dotcom bubble, as investors seek exposure to AI-driven energy demand from data centers.

VarAlign is a VS Code extension that detects duplicate, drifted, or misaligned variables created by AI coding assistants across sessions. It runs 100% locally—no code leaves your machine—and offers views for duplicates, variables, and sessions, along with fix prompt generation and optional AI-powered auto-fix.

Google renames NotebookLM to Gemini Notebook, integrating it more deeply with the Google ecosystem. The tool now supports native code execution for data analysis and cross-app syncing, building on its success as a research and learning aid used by millions.

Gemini Omni and personal avatars in Google Vids make video creation easier than ever.

Mira Murati's Thinking Machines Lab released Inkling, a 975B parameter MoE model (41B active) under Apache-2.0 license, multimodal, trained on 45T tokens. It's not frontier but a strong base for fine-tuning via Tinker platform. Inkling-Small (276B, 12B active) is promised. Model card and training data documentation are unusually brief. Inkling is competitive with Chinese open-weight models, adding to the US ecosystem.

Democr.ai is an open-source, self-hosted agentic AI runtime framework that integrates server-driven UI, multi-client rendering, multi-tenancy, RBAC, OS-level sandboxing, triple-layer audit, pluggable AI engine orchestration, and a knowledge subsystem. Its core philosophy is 'everything is a module,' with no vendor lock-in and security as a primitive. The project is beta but production-oriented.

Chinese AI company StepFun unveils StepX Neo, the world's first agentic AI phone built from the ground up with native AI OS, on-device and cloud processing, and multi-platform task automation.

This article analyzes the impending margin collapse in AI inference due to the rise of 'good enough' cheap models. Winners include the hardware supply chain, hyperscalers, coding agents, and consumers; frontier AI labs face risks but may counter by withholding top models or moving to managed platforms. The overlooked B2C advertising market could also shift dynamics.

Meta launched Muse Spark 1.1, the first Meta model with a price tag, marking a shift from open weights to a closed-source business model. As Meta builds a full vertical stack—from chips to cloud to apps—the question arises whether it can compete with frontier AI labs.

The new body, which will steward the x402 payments protocol, is backed by 40 members including Visa, Mastercard, Google and Microsoft.

Thinky's first full LLM release is a banger and bonus: it's open weights!

The article criticizes the common phrase "AI is just a tool—it matters how you use it," arguing that tools are never neutral. They have politics, shape environments, and influence humanity. Using examples like cars and chairs, the author shows how designs embed values. AI, as a tool, is especially dangerous because it eliminates meaningful struggle, threatening critical thinking and human essence. The piece calls for a critical re-examination of technology beyond simplistic "tool neutrality."

A curated collection of 50+ open-source Next.js AI templates and starter kits covering chatbots, RAG, voice agents, image generation, and more, created by Suhas Bhairav.

cayleyR is an R package for solving permutation puzzles by detecting cycle intersections in Cayley graphs. It uses an iterative bidirectional search and distance-guided bridge selection. The package targets the TopSpin(n,k) puzzle and leverages C++ indexing with optional Vulkan GPU acceleration. It is available on CRAN.

An interactive visual map of 56 AI concepts and their connections, allowing users to explore and learn about key topics in artificial intelligence.

Through the lens of a blues song, the author explores how large language models generate text—often explaining after the fact, but sometimes planning ahead. The article reflects on the 'phony voice' of AI, our drive to strip it bare through interpretability, and the author's own experience using AI to write about AI.

Agentic inference is shifting AI infrastructure from training expansion to context-aware, memory-augmented reasoning. The RAISE Summit highlighted three key insights: specialization across the AI stack with diverse chips and accelerators, storage becoming an active memory extension for GPUs, and the integration of capital deployment and data sovereignty into infrastructure design.

Neocloud provider QumulusAI announced its direct listing on Nasdaq under the ticker QMLS. The move signals the maturation of AI-first infrastructure built around GPUs and power availability. The company focuses on rapid GPU deployment, leveraging colocation and modular data centers. The listing provides capital flexibility, public company credibility, and timing advantage. The article also explores neocloud differentiation and advice for IT leaders.

This article breaks down the real meaning behind reliability numbers like 99%, 99.9%, and 99.99% uptime for AI inference services, explaining the failure domains each tier must survive and the architectural requirements. The authors from Together AI share their experience building reliable inference infrastructure and provide key questions to ask any provider before committing.

Mira Murati's Thinking Machines Lab Inc. today launched its first foundation model with the release of Inkling, making its full open weights available to developers so they can fine-tune it as they wish. Inkling is a mixture-of-experts model with 975 billion parameters (41B active) trained on 45 trillion tokens of text, image, audio and video, capable of reasoning across all four modalities but outputting only text. It features "thinking effort" controls and uncertainty flagging to reduce hallucinations. The model is fine-tunable via the Tinker API and aims to provide a Western open-source alternative to Chinese AI models. Thinking Machines plans to generate revenue through the Tinker platform rather than per-token API access, potentially disrupting current AI business models.

Thinking Machines Lab released Inkling on July 15, 2026, its first model trained from scratch. The full weights ship under Apache 2.0. It is a 975B-parameter Mixture-of-Experts transformer with 41B active parameters, a 1M-token context window, and native text, image, and audio input. The core differentiator is controllable thinking effort, allowing users to adjust token budgets per call to balance cost and performance.

NVIDIA announces T3000 and T2000 modules based on the Thor architecture, targeting mainstream robotics and edge AI. T3000 delivers 865 FP4 teraflops at half the size and power of T5000; T2000 offers 400 FP4 teraflops. The platform scales from 70 TOPS to 2,000 teraflops. New agent skills automate memory optimization, reducing usage by up to 15GB. Cosmos 3 Edge model enables real-time vision. Emulation available now with modules shipping in Q1 2027.

Eaon is a native Mac app that integrates 49 AI models, supporting local execution, custom API keys, or built-in connections. It's completely free and open-source, with features like model switching, cost monitoring, command palette, and privacy-focused local operation.

Cadence Design Systems introduces AuraStack, an AI agent for packaging and PCB design, aiming to automate system design workflows and reduce design time from days to minutes.

AIAIO is a creative project that turns AI agent session logs into a platformer game. Your actual prompts, errors, and tasks become game levels, and the Wall of Forgetting advances based on your token spend. It's both an educational tool and a self-reflection tool.

Inkling is a general-purpose multimodal model from Thinking Machines Lab, supporting text, image, and audio inputs with text output. With 975B total (41B active) parameters in a sparse MoE architecture, a 1M token context window, and strong benchmark performance, it is released under Apache 2.0 with open weights for research and commercial use.

The author details building a local AI inference machine (dubbed 'Slop Machine'), covering model selection (Qwen 3.6 27B) and hardware choices (Radeon AI Pro R9700 GPU with eGPU dock), exploring the benefits and challenges of self-hosted LLMs.

A German research consortium has published the pretraining report for Soofi S 30B-A3B, an open base model for German and English. It is a Mixture-of-Experts hybrid Mamba Transformer model with 31.6B total parameters, activating 3.2B per token. It achieves the highest English and German aggregate scores among tested fully open base models.

Built partnered with the AWS Generative AI Innovation Center, AND Digital, and AWS account teams to create a scalable, AI-powered document processing engine that can classify, split, extract, evaluate, and reason over complex real estate finance documents. It reduces workflows that previously took days to minutes, supports hundreds of document types, and gives technical teams and industry experts a shared environment for building and improving document processors.

IBM has expanded its Power server lineup with new software to automate infrastructure management and application development, including Power Autonomous Operations, the IBM Bob Premium Package for i, and the Power S1112 server for local AI inference. The releases aim to enable autonomous IT capabilities, with projected growth in AI agents driving the need for self-managing infrastructure.

Higher education institutions struggle to scale call center quality assurance for student advisory services. Databricks proposes a GenAI solution using OpenAI Whisper for accurate transcription, LLM-as-a-judge for consistent scoring against rubrics, and AI Functions for enrichment—all on a single governed platform, with insights accessible via natural language through Genie and Agent Bricks.

As AI becomes one of the fastest-growing expenses for US businesses, some startups are switching to cheaper Chinese AI models to cut costs. Despite being behind in capabilities, Chinese models offer cost advantages and open-source availability.

A research team successfully used 14 Macs spread across four countries (including a personal MacBook) for reinforcement learning post-training, achieving a held-out pass@1 improvement from 29% to 63% on PaperSearchQA. The system employs PULSE weight synchronization to compress 9GB updates to ~90MB, and an asynchronous star topology with all communication via object storage—no dedicated networking required. This is the first RL post-training run using only consumer Macs for rollout generation.