Librarians are organizing viral “Avoiding AI” workshops that teach practical strategies for reducing reliance on Big Tech and minimizing exposure to AI-driven surveillance and data harvesting. These sessions focus on concrete alternatives—privacy-preserving tools, open-source software, decentralized services, and low-data workflows—so participants can regain control over personal information and reduce algorithmic influence. Run as free, community-centered programs in public libraries and community hubs, the workshops blend hands-on training (privacy settings, tracker blockers, vetted apps), critical literacy about data collection, and conversations about trade-offs when opting out of mainstream platforms. They have spread rapidly via social media, attracting a wide mix of attendees from seniors and parents to activists and tech skeptics. Organizers emphasize libraries as trusted, noncommercial spaces for digital resilience, while noting challenges around staff training, funding, and scalability. The movement is raising awareness about alternatives to big tech ecosystems and prompting broader discussion on digital choice and civic tech policies.

Midjourney has purchased popular horoscope app Co‑Star in a surprise acquisition, marking a significant expansion of the AI image‑generator company into personalized consumer apps. The deal, announced without prior public hints, brings Co‑Star’s large, engaged user base and its algorithmic astrology features under Midjourney’s ownership; specific financial terms and integration timelines were not disclosed in the announcement. The acquisition signals Midjourney’s intent to broaden beyond generative visuals into more personalized, data‑driven experiences, potentially combining Co‑Star’s astrological insights with new AI‑powered customization and creative features. Reactions among Co‑Star users and privacy advocates were mixed, with curiosity about product improvements tempered by concerns over data handling, changes to algorithms, and the app’s editorial voice. Midjourney said little about staffing or roadmap details, leaving specifics on feature rollouts, privacy safeguards, and monetization strategies unconfirmed as users and industry watchers await further updates.

European social-media researchers warn that major platforms are actively stonewalling independent research by restricting access to data, API functionality, and internal records needed to study harms, misinformation, and algorithmic behavior. Researchers say companies including Meta, X (formerly Twitter), TikTok and YouTube have limited or costly API access, refused to share moderation and recommendation logs, and narrowed researcher programs, making reproducible, large-scale study effectively impossible. These barriers undermine efforts to evaluate platform-driven societal harms and to hold firms accountable for content moderation and recommendation systems. The community is calling for stronger regulatory backing—clear legal mandates, standardized safe-data enclaves, and enforceable data-access requirements under European rules such as the Digital Services Act and GDPR—to ensure auditors and academics can analyze algorithms and moderation practices. Companies defend their decisions on privacy and safety grounds, while policymakers and funders consider tougher oversight, transparency obligations, and penalties to prevent obstruction of independent research and to preserve public-interest investigations into algorithmic effects.

Art museums are using visitor data and analytics to reshape on-site experiences and programming, moving from static exhibitions to dynamic, evidence-driven engagement strategies. Museums are collecting and analyzing data from ticketing systems, Wi‑Fi and beacon signals, mobile apps, sensors, and visitor surveys to build heat maps of movement, understand dwell times, and tailor interpretive content. These insights help curators prioritize works, optimize gallery layouts, and design targeted programming that responds to audience interests and behavior. Institutions are also experimenting with machine learning and computer-vision tools to automate counting, classify modes of engagement, and personalize recommendations, while using natural-language analysis to mine visitor feedback. The shift raises governance and ethics issues—privacy, consent, data ownership, and equitable representation—prompting museums to develop policies, anonymization practices, and partnerships with technologists. Overall, data-driven approaches aim to improve accessibility, measure deeper learning outcomes beyond attendance, and balance commercial pressures with museums’ educational and stewardship missions.

A one-time $80 lifetime subscription is being offered through July 26 for an “advanced business” plan that bundles multiple large-language-model chat assistants — including ChatGPT, Claude, Gemini and others — into a single dashboard. The deal advertises a unified interface to access several AI models from one place, aiming to simplify switching between engines, centralize prompts and histories, and provide power-user features such as advanced prompt templates, exportable chat logs, and model-selection controls. The offer targets freelancers, small teams, and AI-curious users who want broad access without recurring fees, touting cost savings versus multiple paid subscriptions. Potential buyers should verify which model versions and API access are included, check any usage or rate limits, review privacy and data-handling terms, and confirm platform compatibility (web and/or mobile). The sale is time-limited and positioned as a convenient aggregator for people who rely on multiple AI services in their workflows.

Smart Money Stage will spotlight how fintech, payments and AI converge to reshape financial services, bringing together founders, investors, operators and regulators to tackle commercialization, compliance and scaling challenges. The stage programs a mix of panels, fireside chats and demos that focus on payments innovation, embedded finance, buy-now-pay-later evolution, cross-border rails, tokenization and infrastructure modernization, with particular attention to how AI is being applied to underwriting, fraud detection, pricing and customer experience. Attendees can expect deep-dive conversations on regulation and privacy, venture trends and go-to-market strategies, plus onstage investor office hours and startup showcases that connect entrepreneurs with capital and partners. The Smart Money Stage aims to illuminate practical product roadmaps and investment theses, surface emerging categories (AI-native fintech, real-time settlement, identity and data orchestration) and provide actionable takeaways for founders and investors navigating a rapidly changing payments and financial-technology landscape.

Class action lawyers are mounting legal challenges on behalf of independent artists whose work was allegedly scraped and used without consent to train generative AI image models. The lawsuits contend that large-scale data collection and model training have enabled AI systems to reproduce artists’ distinctive styles and undercut their livelihoods without licensing, attribution, or compensation. The reporting highlights artists’ experiences of seeing their styles mimicked, lost commissions, and marketplace displacement, while lawyers pursue claims including copyright infringement and unfair business practices and seek class certification, damages, and injunctions. The piece discusses legal hurdles—such as defendants’ likely fair-use and transformative-use defenses—and explores calls for clearer consent, licensing frameworks, opt-outs, and transparency from model developers. It situates the disputes within broader debates about how to balance innovation in generative AI with creators’ rights and economic survival, and notes the potential for precedent-setting outcomes that could reshape data practices and licensing in the AI industry.

Waymo is reportedly weighing a breakup with Uber, exploring options to unwind or reshape its commercial ties amid strategic and financial disagreements. Sources tell TechCrunch that Alphabet’s self-driving unit has been re-evaluating its partnership structure with Uber’s ride-hail business, considering moves that could include ending revenue-sharing arrangements, pursuing more direct commercial agreements with automakers or ride platforms, or preparing for greater operational independence. The discussions, still described as preliminary, are said to be driven by differing priorities over deployment pace, liability and revenue splits, and Waymo’s push to scale its own product offerings like Waymo One and licensing deals. A separation could complicate Uber’s autonomous plans, shift competitive dynamics among mobility players and influence investor sentiment across the AV sector. TechCrunch reports that both companies have been engaging advisors and that any concrete decisions would take time, with regulatory, contractual and safety implications likely shaping next steps.

Microsoft is reportedly adding a built-in option in Windows 11 to remap the dedicated Copilot key so it can be set to do nothing, giving users a direct way to prevent accidental launches. The change appears in preview channels as an option in keyboard/remapping settings, addressing complaints from users whose keyboards include a Copilot-specific key that opens Microsoft’s AI assistant unexpectedly. The article notes this is part of ongoing tweaks to Copilot integration following user feedback and the proliferation of hardware with a Copilot button. Until now users relied on third-party tools or registry hacks to disable the key; a native setting would simplify customization and reduce accidental interruptions. Microsoft is testing the capability in Insider builds and may roll it out more broadly if feedback is positive. Overall, this is a small but practical quality-of-life improvement for users who prefer not to invoke the AI assistant via a dedicated key.

Researchers used AlphaFold’s protein-structure predictions to redesign gene‑editing proteins and reduce risks associated with off‑target activity and immune recognition. By leveraging high‑accuracy models of candidate editors, the team identified vulnerable regions and proposed sequence changes that preserve catalytic function while altering DNA‑binding affinity and surface features linked to immunogenicity. The article describes how computational redesign guided by AlphaFold allowed prioritization of mutations for experimental testing, accelerating the cycle of design, validation in vitro and in cells, and selection of variants with improved specificity and stability. Results suggest AI‑guided structural insight can make therapeutic editors safer and speed development, though authors and commentators note the need for extensive in vivo studies and regulatory scrutiny before clinical use. The piece frames this work as an early example of integrating deep‑learning structure prediction into practical bioengineering workflows, with implications for gene‑therapy safety and protein design pipelines.

Claude Cookbook serves as an official repository of practical guides, code examples, and recipes designed to help developers effectively integrate Anthropic’s Claude models into their applications. It provides comprehensive documentation on leveraging the API, ranging from basic setup and prompt engineering techniques to advanced implementations like function calling, tool orchestration, and data analysis. Key resources include tutorials on optimizing model performance, managing long-context windows, and building robust AI agents. These practical implementations enable developers to create sophisticated, context-aware workflows, ensuring they can harness the full potential of Claude’s advanced linguistic and reasoning capabilities across diverse technical projects.

Flux 3 X Mimic delivers a step-change in video-action understanding by combining a high-efficiency spatiotemporal backbone (Flux 3) with a purpose-built action modeling head (Mimic) to achieve state-of-the-art accuracy and practical runtime for real-world video tasks. The system emphasizes robust temporal modeling, improved sample efficiency, and deployment-friendly optimization: Flux 3 provides dense, multi-scale temporal attention and lightweight video encoders while Mimic applies contrastive pretraining, cross-modal alignment, and label-efficient fine-tuning to map video representations to action labels and captions. The article details benchmark results showing strong gains on standard action-recognition datasets, ablations that highlight the benefits of temporal attention and distillation, and engineering improvements for lower-latency inference. It also describes practical tooling for fine-tuning, evaluation, and on-device deployment, plus released checkpoints and code to reproduce experiments. Use cases include surveillance analytics, sports understanding, and human-computer interaction, with emphasis on reproducibility and efficient real-time inference for production applications.

Anduril is reportedly in talks to raise funding that would value the defense-software company at about $100 billion, more than three times its valuation from last year. Sources tell TechCrunch that the discussions involve both new institutional investors and existing backers, and that terms and timing remain fluid; the company has not confirmed a deal. If completed, the round would place Anduril alongside the largest private tech valuations and underscore strong investor appetite for firms combining AI, autonomy and defense systems. The story highlights Anduril’s rapid growth as it expands its autonomous systems, sensor networks and Lattice AI software into new government and commercial contracts, boosting revenue expectations that underpin a much higher private-market price. Observers caution the talks may not result in a transaction and that any deal size, investor mix or secondary-selling details could change. A successful raise at this valuation would reshape fundraising benchmarks for defense-focused AI startups and affect comparables across both the defense and AI sectors.

Cognition’s acquisition of Poke signals that configurable AI personality — the ability to give agents consistent, customizable voices and behavioral traits — is emerging as a differentiator in the enterprise AI market. The buy brings Poke’s tooling and design expertise into Cognition’s platform to let customers craft branded, role-specific agent personas that improve user engagement, clarify responses, and speed deployment across support, sales and internal workflows. Poke’s tech focuses on persona templates, prompt engineering workflows, and safety guardrails that make agent behavior predictable and auditable; integrating this into Cognition aims to simplify developer UX, create new monetization levers, and lock in customers through tailored experiences. The article also highlights industry dynamics: rivals are racing to productize persona layers, while ethics and privacy considerations (consent, data retention, and misuse mitigation) will shape adoption. Overall, the move reflects a broader shift from raw capability toward differentiated user experience as a competitive advantage in AI products.

Anthropic has officially unveiled Claude 3.5 Opus, the latest iteration of its flagship large language model, designed to push the boundaries of reasoning and long-context performance. This release integrates advanced architectural refinements that significantly enhance the model's coding capabilities, nuance in creative writing, and accuracy in complex data synthesis. Optimized for professional workflows, the new model introduces improved latency and resource efficiency compared to its predecessors. Anthropic emphasizes that Opus 5 maintains the company’s signature commitment to constitutional AI, ensuring higher levels of steerability and safety when handling enterprise-grade analytical tasks.

Netflix and Prime Video are planning AI-driven homepages to personalize what users see, but many users say they don't want "software to think" for them. Both platforms are experimenting with machine-learning–powered layouts, personalized carousels and content selection intended to boost discovery and engagement by tailoring thumbnails, ordering and recommendations to individual tastes. User testing and feedback reveal resistance: viewers worry about loss of control, opaque algorithms, increased filter bubbles and reduced serendipitous discovery. Many respondents prefer visible choices and the ability to opt out of aggressive personalization, warning that automated curation can misrepresent preferences and narrow viewing horizons. Industry response may include clearer opt-outs, transparency tools and hybrid approaches that combine AI suggestions with human curation. Platforms face a balancing act between using AI to improve relevance and maintaining user trust, agency and diverse content discovery.

The Razer Kiyo V2 succeeds as a high-quality streaming webcam by building upon its predecessor's foundation with a larger sensor and improved overall video fidelity. It provides crisp, natural imagery that performs reliably in various lighting conditions, making it a strong contender for streamers seeking plug-and-play convenience. Despite Razer’s push for AI-integrated software, the internal automated features—such as background removal and auto-framing—often feel secondary to the device's optical performance. These software-based AI tools lack the polished implementation found in competitive products, offering limited practical value for professional users. Ultimately, the hardware quality justifies the purchase, even if the marketing focus on AI falls short of being a significant selling point.

AI companies are pressing to accelerate construction of large-scale data centers to support compute-hungry models, while the Trump administration’s EPA is proposing or implementing regulatory changes that could reduce local communities’ ability to influence siting and permitting decisions. The push for more centers is driven by soaring demand for electricity, cooling, and networking capacity from generative-AI training and inference workloads; firms and utilities emphasize economic benefits, job creation, and national competitiveness, but residents and environmental groups warn of increased energy consumption, strain on water supplies, heat-island effects, and sprawling industrial footprints. At the same time, the EPA actions described would narrow public input windows, streamline permitting, and shift review authority in ways that critics say prioritize industry speed over environmental review and community concerns. Supporters argue the changes remove bureaucratic delays and help secure critical infrastructure, while opponents fear diminished transparency and weakened oversight of pollution, habitat impacts, and local planning. The article frames this as a clash between rapid AI infrastructure buildout and protections for affected communities and ecosystems.

Sam Altman’s biometric startup World raised $52.5 million through a cryptocurrency token sale to fund product development and growth. The raise, conducted via a token offering rather than a traditional venture round, provides liquidity and capital for World’s ambitions in biometric-based identity and passwordless authentication. World is building biometric identity infrastructure that emphasizes on-device matching, cryptographic proofs and developer-facing tools to enable apps to verify users without centralizing raw biometric data. The fundraising route highlights a broader trend of startups using token sales to accelerate product roadmaps while offering community participation, but it also draws scrutiny from privacy advocates and regulators. Observers flagged concerns about biometric data use, governance of token-driven platforms, and securities implications of the sale. World plans to deploy funds into engineering, partnerships and regulatory compliance as it scales, while balancing privacy-preserving technical designs with commercial integrations and market adoption.

The current state of the software industry is characterized by an illusion of productivity, where widespread technical debt and broken systems are masked by excessive optimism. Despite the prevalence of failing tools and inefficient processes, companies and developers alike maintain a sense of irrational exuberance, often prioritizing the appearance of innovation over functional stability. This phenomenon is driven by a disconnect between high-level hype and the ground-level reality of day-to-day operations. When fundamental infrastructure becomes increasingly brittle, the industry relies on a culture of 'success theater' to sustain momentum. Ultimately, the cycle suggests that true technological progress is being substituted by performative growth and the normalization of systemic failure.