
Trump AI Czar Is Trying to Take Down Anthropic AI
David Sacks is at it again.
David Sacks is at it again.
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It's designed for content creators and professionals. The post ASUS’ Newest ProArt Monitor Comes Priced at $8,000 appeared first on Phandroid .
Commentary: This cowboy drama has a stellar cast and strong script, and the ending is an unsettling display of terror that'll leave your jaw on the floor.
Anthropic released Claude Haiku 4.5 on Wednesday, a smaller and significantly cheaper artificial intelligence model that matches the coding capabilities of systems that were considered cutting-edge just months ago, marking the latest salvo in an intensifying competition to dominate enterprise AI. The model costs $1 per million input tokens and $5 per million output tokens — roughly one-third the price of Anthropic's mid-sized Sonnet 4 model released in May, while operating more than twice as fast. In certain tasks, particularly operating computers autonomously, Haiku 4.5 actually surpasses its more expensive predecessor. "Haiku 4.5 is a clear leap in performance and is now largely as smart as Sonnet 4 while being significantly faster and one-third of the cost," an Anthropic spokesperson told VentureBeat, underscoring how rapidly AI capabilities are becoming commoditized as the technology matures. The launch comes just two weeks after Anthropic released Claude Sonnet 4.5 , which the company bills as the world's best coding model, and two months after introducing Opus 4.1. The breakneck pace of releases reflects mounting pressure from OpenAI, whose $500 billion valuation dwarfs Anthropic's $183 billion , and which has inked a series of multibillion-dollar infrastructure deals while expanding its product lineup. How free access to advanced AI could reshape the enterprise market In an unusual move that could reshape competitive dynamics in the AI market, Anthropic is making Haiku 4.5 available for all free users of its Claude.ai platform. The decision effectively democratizes access to what the company characterizes as "near-frontier-level intelligence" — capabilities that would have been available only in expensive, premium models months ago. "The launch of Claude Haiku 4.5 means that near-frontier-level intelligence is available for free to all users through Claude.ai," the Anthropic spokesperson told VentureBeat. "It also offers significant advantages to our enterprise customers: Sonnet 4.5 can handle frontier planning while Haiku 4.5 powers sub-agents, enabling multi-agent systems that tackle complex refactors, migrations, and large features builds with speed and quality." This multi-agent architecture signals a significant shift in how AI systems are deployed. Rather than relying on a single, monolithic model, enterprises can now orchestrate teams of specialized AI agents: a more sophisticated Sonnet 4.5 model breaking down complex problems and delegating subtasks to multiple Haiku 4.5 agents working in parallel. For software development teams, this could mean Sonnet 4.5 plans a major code refactoring while Haiku 4.5 agents simultaneously execute changes across dozens of files. The approach mirrors how human organizations distribute work, and could prove particularly valuable for enterprises seeking to balance performance with cost efficiency — a critical consideration as AI deployment scales. Inside Anthropic's path to $7 billion in annual revenue The model launch coincides with revelations that Anthropic's business is experiencing explosive growth. The company's annual revenue run rate is approaching $7 billion this month , Anthropic told Reuters, up from more than $5 billion reported in August. Internal projections obtained by Reuters suggest the company is targeting between $20 billion and $26 billion in annualized revenue for 2026, representing growth of more than 200% to nearly 300%. The company now serves more than 300,000 business customers, with enterprise products accounting for approximately 80% of revenue. Among Anthropic's most successful offerings is Claude Code , a code-generation tool that has reached nearly $1 billion in annualized revenue since launching earlier this year. Those numbers come as artificial intelligence enters what many in the industry characterize as a critical inflection point. After two years of what Anthropic Chief Product Officer Mike Krieger recently described as " AI FOMO " — where companies adopted AI tools without clear success metrics — enterprises are now demanding measurable returns on investment. "The best products can be grounded in some kind of success metric or evaluation," Krieger said on the "Superhuman AI" podcast . "I've seen that a lot in talking to companies that are deploying AI." For enterprises evaluating AI tools, the calculus increasingly centers on concrete productivity gains. Google CEO Sundar Pichai claimed in June that AI had generated a 10% boost in engineering velocity at his company — though measuring such improvements across different roles and use cases remains challenging, as Krieger acknowledged. Why AI safety testing matters more than ever for enterprise adoption Anthropic's launch comes amid heightened scrutiny of the company's approach to AI safety and regulation. On Tuesday, David Sacks, the White House's AI "czar" and a venture capitalist, accused Anthropic of " running a sophisticated regulatory capture strategy based on fear-mongering" that is "damaging the startup ecosystem ." The attack targeted remarks by Jack Clark, Anthropic's British co-founder and head of policy, who had described being " deeply afraid " of AI's trajectory. Clark told Bloomberg he found Sacks' criticism " perplexing ." Anthropic addressed such concerns head-on in its release materials, emphasizing that Haiku 4.5 underwent extensive safety testing. The company classified the model as ASL-2 — its AI Safety Level 2 standard — compared to the more restrictive ASL-3 designation for the more powerful Sonnet 4.5 and Opus 4.1 models. "Our teams have red-teamed and tested our agentic capabilities to the limits in order to assess whether it can be used to engage in harmful activity like generating misinformation or promoting fraudulent behavior like scams," the spokesperson told VentureBeat. "In our automated alignment assessment, it showed a statistically significantly lower overall rate of misaligned behaviors than both Claude Sonnet 4.5 and Claude Opus 4.1 — making it, by this metric, our safest model yet." The company said its safety testing showed Haiku 4.5 poses only limited risks regarding the production of chemical, biological, radiological and nuclear weapons. Anthropic has also implemented classifiers designed to detect and filter prompt injection attacks, a common method for attempting to manipulate AI systems into producing harmful content. The emphasis on safety reflects Anthropic's founding mission. The company was established in 2021 by former OpenAI executives, including siblings Dario and Daniela Amodei, who left amid concerns about OpenAI's direction following its partnership with Microsoft. Anthropic has positioned itself as taking a more cautious, research-oriented approach to AI development. Benchmark results show Haiku 4.5 competing with larger, more expensive models According to Anthropic's benchmarks, Haiku 4.5 performs competitively with or exceeds several larger models across multiple evaluation criteria. On SWE-bench Verified , a widely used test measuring AI systems' ability to solve real-world software engineering problems, Haiku 4.5 scored 73.3% — slightly ahead of Sonnet 4's 72.7% and close to GPT-5 Codex's 74.5%. The model demonstrated particular strength in computer use tasks, achieving 50.7% on the OSWorld benchmark compared to Sonnet 4's 42.2%. This capability allows the AI to interact directly with computer interfaces — clicking buttons, filling forms, navigating applications — which could prove transformative for automating routine digital tasks. In coding-specific benchmarks like Terminal-Bench , which tests AI agents' ability to complete complex software tasks using command-line tools, Haiku 4.5 scored 41.0%, trailing only Sonnet 4.5's 50.0% among Claude models. The model maintains a 200,000-token context window for standard users, with developers accessing the Claude Developer Platform able to use a 1-million-token context window. That expanded capacity means the model can process extremely large codebases or documents in a single request — roughly equivalent to a 1,500-page book. What three major AI model releases in two months says about the competition When asked about the rapid succession of model releases, the Anthropic spokesperson emphasized the company's focus on execution rather than competitive positioning. "We're focused on shipping the best possible products for our customers — and our shipping velocity speaks for itself," the spokesperson said. "What was state-of-the-art just five months ago is now faster, cheaper, and more accessible." That velocity stands in contrast to the company's earlier, more measured release schedule. Anthropic appeared to have paused development of its Haiku line after releasing version 3.5 at the end of last year, leading some observers to speculate the company had deprioritized smaller models. That rapid price-performance improvement validates a core promise of artificial intelligence: that capabilities will become dramatically cheaper over time as the technology matures and companies optimize their models. For enterprises, it suggests that today's budget constraints around AI deployment may ease considerably in coming years. From customer service to code: Real-world applications for faster, cheaper AI The practical applications of Haiku 4.5 span a wide range of enterprise functions, from customer service to financial analysis to software development. The model's combination of speed and intelligence makes it particularly suited for real-time, low-latency tasks like chatbot conversations and customer support interactions, where delays of even a few seconds can degrade user experience. In financial services, the multi-agent architecture enabled by pairing Sonnet 4.5 with Haiku 4.5 could transform how firms monitor markets and manage risk. Anthropic envisions Haiku 4.5 monitoring thousands of data streams simultaneously — tracking regulatory changes, market signals and portfolio risks — while Sonnet 4.5 handles complex predictive modeling and strategic analysis. For research organizations, the division of labor could compress timelines dramatically. Sonnet 4.5 might orchestrate a comprehensive analysis while multiple Haiku 4.5 agents parallelize literature reviews, data gathering and document synthesis across dozens of sources, potentially "compressing weeks of research into hours," according to Anthropic's use case descriptions. Several companies have already integrated Haiku 4.5 and reported positive results. Guy Gur-Ari, co-founder of coding startup Augment, said the model "hit a sweet spot we didn't think was possible: near-frontier coding quality with blazing speed and cost efficiency." In Augment's internal testing, Haiku 4.5 achieved 90% of Sonnet 4.5's performance while matching much larger models. Jeff Wang, CEO of Windsurf, another coding-focused startup, said Haiku 4.5 "is blurring the lines" on traditional trade-offs between speed, cost and quality. "It's a fast frontier model that keeps costs efficient and signals where this class of models is headed." Jon Noronha, co-founder of presentation software company Gamma, reported that Haiku 4.5 "outperformed our current models on instruction-following for slide text generation, achieving 65% accuracy versus 44% from our premium tier model — that's a game-changer for our unit economics." The price of progress: What plummeting AI costs mean for enterprise strategy For enterprises evaluating AI strategies, Haiku 4.5 presents both opportunity and challenge. The opportunity lies in accessing sophisticated AI capabilities at dramatically lower costs, potentially making viable entire categories of applications that were previously too expensive to deploy at scale. The challenge is keeping pace with a technology landscape that is evolving faster than most organizations can absorb. As Krieger noted in his recent podcast appearance, companies are moving beyond " AI FOMO " to demand concrete metrics and demonstrated value. But establishing those metrics and evaluation frameworks takes time — time that may be in short supply as competitors race ahead. The shift from single-model deployments to multi-agent architectures also requires new ways of thinking about AI systems. Rather than viewing AI as a monolithic assistant, enterprises must learn to orchestrate multiple specialized agents, each optimized for particular tasks — more akin to managing a team than operating a tool. The fundamental economics of AI are shifting with remarkable speed. Five months ago, Sonnet 4's capabilities commanded premium pricing and represented the cutting edge. Today, Haiku 4.5 delivers similar performance at a third of the cost. If that trajectory continues — and both Anthropic's release schedule and competitive pressure from OpenAI and Google suggest it will — the AI capabilities that seem remarkable today may be routine and inexpensive within a year. For Anthropic, the challenge will be translating technical achievements into sustainable business growth while maintaining the safety-focused approach that differentiates it from competitors. The company's projected revenue growth to as much as $26 billion by 2026 suggests strong market traction, but achieving those targets will require continued innovation and successful execution across an increasingly complex product portfolio. Whether enterprises will choose Claude over increasingly capable alternatives from OpenAI, Google and a growing field of competitors remains an open question. But Anthropic is making a clear bet: that the future of AI belongs not to whoever builds the single most powerful model, but to whoever can deliver the right intelligence, at the right speed, at the right price — and make it accessible to everyone. In an industry where the promise of artificial intelligence has long outpaced reality, Anthropic is betting that delivering on that promise, faster and cheaper than anyone expected, will be enough to win. And with pricing dropping by two-thirds in just five months while performance holds steady, that promise is starting to look like reality.
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Tiny, fast model hits coding scores similar to GPT-5 and Sonnet 4.
How weren't these already a thing?
As expected after days of leaks and rumors online, Google has unveiled Veo 3.1 , its latest AI video generation model, bringing a suite of creative and technical upgrades aimed at improving narrative control, audio integration, and realism in AI-generated video. While the updates expand possibilities for hobbyists and content creators using Google’s online AI creation app, Flow , the release also signals a growing opportunity for enterprises, developers, and creative teams seeking scalable, customizable video tools. The quality is higher, the physics better, the pricing the same as before, and the control and editing features more robust and varied. My initial tests showed it to be a powerful and performant model that immediately delights with each generation. However, the look is more cinematic, polished and a little more "artificial" than by default than rivals such as OpenAI's new Sora 2 , released late last month, which may or may not be what a particular user is going after (Sora excels at handheld and "candid" style videos). Expanded Control Over Narrative and Audio Veo 3.1 builds on its predecessor, Veo 3 ( released back in May 2025 ) with enhanced support for dialogue, ambient sound, and other audio effects. Native audio generation is now available across several key features in Flow, including “Frames to Video,” “Ingredients to Video,” and “Extend," which give users the ability to, respectively: turn still images into video; use items, characters and objects from multiple images in a single video; and generate longer clips than the initial 8 seconds, to more than 30 seconds or even 1+ plus when continuing from a prior clip's final frame. Before, you had to add audio manually after using these features. This addition gives users greater command over tone, emotion, and storytelling — capabilities that have previously required post-production work. In enterprise contexts, this level of control may reduce the need for separate audio pipelines, offering an integrated way to create training content, marketing videos, or digital experiences with synchronized sound and visuals. Google noted in a blog post that the updates reflect user feedback calling for deeper artistic control and improved audio support. Gallegos emphasizes the importance of making edits and refinements possible directly in Flow, without reworking scenes from scratch. Richer Inputs and Editing Capabilities With Veo 3.1, Google introduces support for multiple input types and more granular control over generated outputs. The model accepts text prompts, images, and video clips as input, and also supports: Reference images (up to three) to guide appearance and style in the final output First and last frame interpolation to generate seamless scenes between fixed endpoints Scene extension that continues a video’s action or motion beyond its current duration These tools aim to give enterprise users a way to fine-tune the look and feel of their content—useful for brand consistency or adherence to creative briefs. Additional capabilities like “Insert” (add objects to scenes) and “Remove” (delete elements or characters) are also being introduced, though not all are immediately available through the Gemini API. Deployment Across Platforms Veo 3.1 is accessible through several of Google’s existing AI services: Flow , Google’s own interface for AI-assisted filmmaking Gemini API , targeted at developers building video capabilities into applications Vertex AI , where enterprise integration will soon support Veo’s “Scene Extension” and other key features Availability through these platforms allows enterprise customers to choose the right environment—GUI-based or programmatic—based on their teams and workflows. Pricing and Access The Veo 3.1 model is currently in preview and available only on the paid tier of the Gemini API. The cost structure is the same as Veo 3, the preceding generation of AI video models from Google. Standard model : $0.40 per second of video Fast model : $0.15 per second There is no free tier, and users are charged only if a video is successfully generated. This model is consistent with previous Veo versions and provides predictable pricing for budget-conscious enterprise teams. Technical Specs and Output Control Veo 3.1 outputs video at 720p or 1080p resolution , with a 24 fps frame rate . Duration options include 4, 6, or 8 seconds from a text prompt or uploaded images, with the ability to extend videos up to 148 seconds (more than 2 and half minutes!) when using the “Extend” feature. New functionality also includes tighter control over subjects and environments. For example, enterprises can upload a product image or visual reference, and Veo 3.1 will generate scenes that preserve its appearance and stylistic cues across the video. This could streamline creative production pipelines for retail, advertising, and virtual content production teams. Initial Reactions The broader creator and developer community has responded to Veo 3.1’s launch with a mix of optimism and tempered critique—particularly when comparing it to rival models like OpenAI’s Sora 2. Matt Shumer, an AI founder of Otherside AI/Hyperwrite, and early adopter, described his initial reaction as “disappointment,” noting that Veo 3.1 is “noticeably worse than Sora 2” and also “quite a bit more expensive.” However, he acknowledged that Google’s tooling—such as support for references and scene extension—is a bright spot in the release. Travis Davids , a 3D digital artist and AI content creator, echoed some of that sentiment. While he noted improvements in audio quality, particularly in sound effects and dialogue, he raised concerns about limitations that remain in the system. These include the lack of custom voice support, an inability to select generated voices directly, and the continued cap at 8-second generations—despite some public claims about longer outputs. Davids also pointed out that character consistency across changing camera angles still requires careful prompting, whereas other models like Sora 2 handle this more automatically. He questioned the absence of 1080p resolution for users on paid tiers like Flow Pro and expressed skepticism over feature parity. On the more positive end, @kimmonismus, an AI newsletter writer, stated that “Veo 3.1 is amazing,” though still concluded that OpenAI’s latest model remains preferable overall. Collectively, these early impressions suggest that while Veo 3.1 delivers meaningful tooling enhancements and new creative control features, expectations have shifted as competitors raise the bar on both quality and usability. Adoption and Scale Since launching Flow five months ago, Google says over 275 million videos have been generated across various Veo models. The pace of adoption suggests significant interest not only from individuals but also from developers and businesses experimenting with automated content creation. Thomas Iljic, Director of Product Management at Google Labs, highlights that Veo 3.1’s release brings capabilities closer to how human filmmakers plan and shoot. These include scene composition, continuity across shots, and coordinated audio—all areas that enterprises increasingly look to automate or streamline. Safety and Responsible AI Use Videos generated with Veo 3.1 are watermarked using Google’s SynthID technology, which embeds an imperceptible identifier to signal that the content is AI-generated. Google applies safety filters and moderation across its APIs to help minimize privacy and copyright risks. Generated content is stored temporarily and deleted after two days unless downloaded. For developers and enterprises, these features provide reassurance around provenance and compliance—critical in regulated or brand-sensitive industries. Where Veo 3.1 Stands Among a Crowded AI Video Model Space Veo 3.1 is not just an iteration on prior models—it represents a deeper integration of multimodal inputs, storytelling control, and enterprise-level tooling. While creative professionals may see immediate benefits in editing workflows and fidelity, businesses exploring automation in training, advertising, or virtual experiences may find even greater value in the model’s composability and API support. The early user feedback highlights that while Veo 3.1 offers valuable tooling, expectations around realism, voice control, and generation length are evolving rapidly. As Google expands access through Vertex AI and continues refining Veo, its competitive positioning in enterprise video generation will hinge on how quickly these user pain points are addressed.
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Roku just announced a robust software update coming to many of its devices. These are free upgrades, with search getting a major AI boost. First of all, the pre-existing voice search feature is getting "AI smarts." This means that users will be able to ask contextual questions about movies, actors and shows. It's worth noting that the bot will deliver the answers on-screen and not via a digital voice. This can be used to help find something to watch, as Roku gives examples of people asking how scary a movie is or if something is safe for children to watch. Roku A search bar is being added to the live TV page and it will scour all of the platform's free live channels to find a match. The search tool will also now give more accurate information as to which streaming platform to choose based on active subscriptions and what people are looking for. The dedicated Roku Sports page will be able to track live scores and will let viewers keep tabs on multiple games at once, thanks to matchup tiles. This can be shut off to keep things spoiler-free. Roku The company's pre-existing Bluetooth Headphone Mode is rolling out to more devices, including the Roku Streaming Stick and Streaming Stick Plus. This lets people connect headphones directly without having to use the dedicated app. Both of those made our list of the best streaming devices , so more functionality is always appreciated. Roku The app is getting an overhaul, with new shortcuts and the ability to rate shows and movies directly within the app. The company has also revealed that Philips Ambilight technology is now available on Roku TVs in the US. This tech automatically changes the ambient lighting based on what's being shown on-screen. All of these software updates will be available to Roku devices in the coming months. The company also recently refreshed many of its midrange TVs with pro-level features . New Roku Plus Series TVs now allow for hands-free voice control and a feature that automatically adjusts the picture on a scene-by-scene basis. This article originally appeared on Engadget at https://www.engadget.com/home/home-theater/the-latest-roku-update-adds-ai-powered-voice-control-and-better-search-184513277.html?src=rss
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Your votes in our poll reveal how much patience is left for the smart home ecosystem.
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