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Anthropic’s IPO draft prospectus — leaked to The Wall Street Journal yesterday — showed that the company is having trouble securing enough cloud capacity from AWS, Google, and Microsoft, which increasingly see the Claude-maker as a competitor rather than a customer. The San Francisco-based company reported $16.3 billion in revenue during that same period, with only two customers accounting for about a fifth of sales. Along with a long list of risk factors, including a narrow customer base, the S-1 filing also disclosed a net loss of $80.7 billion for the first half of 2026. Anthropic is generating breakneck revenue growth but faces a long list of risks and uncertain access to much-needed computing power As it prepares for a mega-IPO in November, Anthropic revealed it could spend more than $750 billion on cloud contracts, some still under negotiation. Building on earlier catastrophic risk disclosures, the filing also warns that Anthropic could be held liable for damages caused by harmful AI behavior in amounts that could exceed available insurance coverage.  

Stay Tuned NOW Streaming Behind The Scenes! – Oct 20

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NVIDIA released Nemotron 3.5 Super VL, a 120-billion-parameter open-source model that the company said can work across PDFs, charts, tables, images, and webpages while following instructions and using tools. It’s a customizable multimodal system for specialized workflows, with a 120B-parameter mixture-of-experts (MoE) architecture that activates 12B parameters per token, balancing model capacity with inference efficiency. It comes with always-on agents designed for taking on longer, more complex enterprise workflows. The model combines reasoning, instruction following, and tool use with text, image, document, and video understanding. Coding: Test and validate code, analyze errors, and recommend fixes. Web research: Search across websites, connect information, and verify answers. Document intelligence: Extract information from tables, charts, and page layouts to produce summaries and reports. Cybersecurity: Identify security vulnerabilities and triage threats to prioritize remediation. Video understanding: Extract information for search, content review, and incident analysis. By combining these capabilities into a single model, teams can handle text and visual tasks without deploying separate text and vision-language models or passing task context between them. For example, a single request can involve reading a document, checking information across sources, following company policy, and calling several tools. Another example, before producing a useful answer, can be reviewing a credit agreement to extract figures from tables, interpret a chart, check a related webpage, and apply the company’s own rules. On a single GPU, this model delivers up to 5x higher throughput for agentic tasks compared to other open models in its size category. Developers can post-train Nemotron 3.5 Super VL with NVIDIA NeMo using their own data, tools, policies, and workflows. This model was also optimized to run locally on NVIDIA DGX Spark. Several NVIDIA partners supported customization and deployment of Nemotron 3.5 Super VL for domain-specific workflows. AfterQuery AgileRL AI21 Alice Applied Compute Baseten Bespoke Labs Databricks distil labs Fastino Labs Fireworks AI Handshake Mercor Mindbeam ms-swift Multiverse Computing Prime Intellect Reasonable River AI Scale AI Thinking Machines Lab (Tinker) TNG Trajectory Inference software Actual Computer Canonical Exo LM Studio Ollama SGLang Unsloth vLLM Harnesses and agent frameworks Aible Cline Hermes Agent Kilo Code LangChain LM Studio Bionic OpenClaw OpenCode OpenHands Pi Cloud platforms Amazon SageMaker JumpStart Google Cloud Gemini Enterprise Agent Platform MSFT Foundry OCI Enterprise AI Global systems integrators HCLTech Infosys Tata Consultancy Services Thoughtworks Hardware and infrastructure Dell HPE Services Red Hat AI natives APMIC Cognition Daily Domyn Dream Eon Factory AI H Company Harvey Inflection AI Navan NextLM NYB.AI Orca Security Perplexity Ramp Terray Two Delta Versos Hosted inference service providers Baseten Bitdeer AI BLACKBOX.AI CoreWeave Crusoe DeepInfra DigitalOcean fal.ai Fireworks AI FriendliAI GMI Cloud Lambda Modal Nebius Nscale Together AI

Stay Tuned NOW Streaming Behind The Scenes! – Oct 19

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High-profile AI startup Character.AI filed for bankruptcy last week, with the goal of reaching a global resolution of all legal claims it received, including lawsuits alleging the company’s chatbots pushed children to suicide and ​self-harm. Character.AI also said it agreed to sell some assets to Walt Disney for $20 million. US states had sued the company multiple times, with Kentucky alleging that its chatbots encouraged users to cut, starve, or ​kill themselves and Pennsylvania alleging its chatbots posed as doctors. Character.AI reached preliminary settlements in five private lawsuits in January. ⁠However, recent court documents from those five cases indicated that the settlements had ​not yet been finalized or paid. Two former Google employees founded Character.AI in 2021. In 2024, Google licensed Character.AI’s technology and rehired the founders. The company has not been profitable, despite having ​roughly 12 million active users. ⁠It was operating at a loss of approximately $8 million to $9 million per month, according to court documents filed in the Wilmington, Delaware, bankruptcy court. Character Technologies, its US-based owner, listed estimated assets and liabilities of between $50 million and $100 million, according to a court filing. The platform will continue to operate during the bankruptcy, but may be shut down if it can’t find a buyer, the company said.  

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