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Hackers are deceiving recruiters by masquerading as job seekers and submitting fake resumes that contain harmful files, which can compromise a company's system when opened.
Over 40,000 security cameras globally are accessible online, enabling hackers to potentially view or exploit live footage, particularly in homes and offices where security is often weak or non-existent.
Ad revenue from user-generated content is projected to surpass that of traditional media for the first time, marking a major turning point in how audiences consume and advertisers value content. Revenue from creator-generated content is expected to grow by 20% this year and more than double by 2030, reaching $376.6 billion as creators attract larger brand deals, ad partnerships, and sponsorships. As creators invest more in production quality and scale their operations, the distinction between independent creators and traditional media companies will continue to blur, making the term creator economy feel outdated as it evolves into a unified media ecosystem
A new report from Ahrefs found that 87% of marketers use AI for content creation, allowing them to publish 42% more content monthly compared to those who do not use AI. ChatGPT is the most used AI tool at 44%, followed by Gemini and Claude. Blog posts are the most common AI-generated content type (87%), and top tasks include brainstorming (76%), outlining (73%), and updating (67%). Despite the prevalence of AI, only 4% publish unedited AI content, and 97% edit or review outputs, with 80% doing so manually. Just 16% of companies disclose their use of AI in content.
ChatGPT's adoption outpaced Google and Facebook in their early years. While usage costs are falling, training costs continue to rise. OpenAI and Google are monetizing through subscriptions, APIs, ads, and embedded AI tools. Horizontal platforms are enabling broad integration, while industry-specific vendors offer tailored solutions. Closed-source models lead for their usability and familiarity, but open-source alternatives are gaining ground among developers seeking flexibility and lower costs. Chinese AI models are narrowing the gap with US counterparts, supported by local demand, lower training expenses, and a more positive public view of AI.
LinkedIn has shifted from a professional network to a content-first platform where brands showcase thought leadership and engage audiences with substance. Companies like Figma, Sephora, and Duolingo have built strong followings by creating content that reflects their company culture, shares relevant industry perspectives, and responds quickly to current events. Their success comes from consistently publishing a mix of content formats such as short posts, videos, and commentary while maintaining a recognizable tone that builds familiarity and trust over time.
Google now synthesizes answers by combining content chunks that respond to multiple related queries, rather than just the one typed by the user. A piece of content does not need to win the original query to be featured in AI Mode as long as it addresses one of the supporting angles like pricing, integrations, or user needs. Marketers must think in terms of micro-answer engine optimization where small, targeted passages can secure visibility across a range of cascading queries.
This guide reviews new ad formats across platforms including Fubo, YouTube, Netflix, Google, Meta, and Twitch. It focuses on optimized timing to capture micro-moments. The guide highlights innovations such as programmatic pause ads, split-screen livestream ads, AI-powered creative integration, and moves toward fully automated ad campaigns.
Pinterest's auto-collages feature quickly creates thousands of shoppable visual collages from product catalogs. It groups items into outfit ideas, popular user collages, similar products, or personalized picks based on saves. The upgraded Trends tool uses AI to analyze searches, saves, and shopping habits. This will help brands predict what consumers will buy, spot top trends, and gain cultural insights to guide their campaigns.
This essay from Sam Altman reflects on how AI has already passed the point of no return. By 2026, AI may generate new discoveries or ideas that humans have not yet uncovered. By 2027, humanoid robots could perform real-world tasks. By 2030, people may achieve far more than they could a decade earlier. The 2030s could bring abundant intelligence and energy, enabling breakthroughs in space and brain-computer interfaces. Challenges like safety, alignment, and fair access remain. However, Altman believes society can adapt by sharing AI widely and focusing on collective goals.
Lyft increased annual revenue by 31% and reached profitability for the first time by centering its turnaround strategy on deep customer understanding. Leadership prioritized firsthand experiences, including the CEO regularly driving and holding roundtables with drivers across cities like New York and San Francisco. This led to features like Price Lock to ease rider frustration with surge pricing, Women Plus Connect to improve safety and comfort for female users, and Restroom Finder to address driver dignity, all reinforcing Lyft's mission to serve both sides of its marketplace.
A witty video of Ritual's campaign in a world full of fakes.
Takeaways from Neopets' revival playbook.
Lyft processes 100 million ML predictions daily through LyftLearn Serving, a platform that replaced a problematic monolithic service with isolated microservices where each team owns their own model serving infrastructure. The system handles real-time predictions for ride pricing, fraud detection, and ETAs using a Flask/Gunicorn HTTP layer with custom predict/load functions that support any ML framework.
API design must evolve for AI consumers, which combine machine precision with human-like understanding and create new constraints like token economics, high latency, and non-deterministic behavior. This means new APIs should be designed for self-healing through rich error messages, treating documentation as runtime code since AI references it continuously, and optimizing for batching and streaming to handle AI's multi-second processing times.
You usually know within the first week if a job is a good fit. Alignment for managers is especially important, as their role requires them to represent and believe in the company's values.
Unlike agentless LLMs that act like a virtual whiteboard, agents can use tools like bash, patch, and web search to navigate codebases, fix errors using compiler feedback, and improve API usage. While agents are great for handling larger codebases and automating tasks, they also have downsides like increased time and token consumption. Also, containers should be used to solve agent safety issues and allow for the parallel running of agents.
Fine-tuning advanced LLMs for knowledge injection is a waste of time and potentially destructive. Updating neurons in these models can overwrite existing valuable knowledge, leading to unintended consequences.
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Lingo.dev is an open-source, AI-powered i18n toolkit designed for instant localization using LLMs. It offers a compiler for build-time React localization, a CLI for translating various content formats, CI/CD for automated translation workflows, and an SDK for real-time, per-request translation of dynamic content.
Rowboat is an AI-powered platform that lets users quickly build multi-agent workflows using tools, integrate them into applications via HTTP API or Python SDK, and use features like RAG and custom LLM providers.
Canva now expects engineering candidates to use AI tools during technical interviews, replacing traditional coding questions that AI can solve easily with complex, ambiguous problems. It evaluates how well candidates collaborate with AI strategically by breaking down requirements, critically reviewing generated code, and making sound technical decisions.
Sentry offers an MCP server, allowing LLMs to access valuable context about application issues directly from Sentry. The Sentry MCP has features like remote hosting, OAuth authentication, streamable HTTP, and various tool calls for accessing project information and issues, and even using Sentry's AI agent Seer. This lets LLMs provide more informed and accurate responses by using real-time Sentry data.
Anthropic recently cut off AI IDE Windsurf's access to its Claude models, betting that developers would follow the most capable models and move to Cursor. Anthropic did this as a move against its chief rival OpenAI, which is set to acquire Windsurf in a $3B deal.
React Hook Form is better for simpler forms and projects where stability is a priority, while TanStack Form is better for complex forms and large-scale applications.
The first major disaster caused by AI language models is likely imminent, potentially involving AI agents automating harmful actions like debt recovery or healthcare denial.
PostHog is creating DeskHog, an open-source, 3D-printed, palm-sized device packed with features for developers to hack, play games, and access PostHog data.
Markdown Ninja is a markdown-first, open-source CMS for bloggers, minimalists, and startups to easily publish websites and newsletters.
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Here's your chance to get actionable frameworks and hard-earned lessons you won't find in traditional playbooks.
Meta is finalizing a deal to invest $14 billion into Scale AI, a company that helps AI startups prepare data to train cutting-edge AI models. Meta is one of Scale AI's biggest customers. The social media giant appears to be taking a similar strategy as other tech companies like Google and Microsoft which are taking large stakes in prominent leaders in AI rather than buying them outright - Meta is currently on trial for antitrust claims and it doesn't want to further upset regulators by acquiring Scale AI. It will take a 49% stake in Scale AI, and Scale AI's CEO will help lead a new AI research lab within Meta.
OpenAI has launched o3-pro, an advanced reasoning model, to ChatGPT Pro and Team users, as well as on OpenAI's developer API. Enterprise and Edu users will get access to the model next week. o3-pro is priced at $20 per million input tokens and $80 per million output tokens on the API. The model has access to tools and can search the web, analyze files, reason about visual inputs, use Python, personalize its responses using memory, and more. It can not generate images or use Canvas and its responses typically take longer than o1-pro to complete.
IBM has released plans for a quantum compute system that can perform 100 million operations without errors on a collection of 200 logical qubits. The hardware, which will be called Starling, will be available for use in 2029. While the system will be able to handle some problems, it will not be enough to perform the complex algorithms needed to do things like break encryptions - that would require waiting for IBM's Blue Jay, a system with 2,000 logical qubits the company expects to build by 2033.
Snap plans to release a sixth generation of its augmented reality glasses in 2026. The next-generation glasses will be called Specs and use AR technology to let people see and interact with digital imagery overlaid over the physical world. It will run on Snap OS. Developers will be able to incorporate Google's Gemini AI models and OpenAI's GPT family of AI models into programs they develop for the smart glasses. The most recent version of Snap's augmented reality glass was released in September 2024 to developers who had to pay $99 a month for a full year under a leasing model.
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Delve ran 4 placements across 2 TLDR newsletters and brought in 66 leads, with a meaningful chunk from enterprise. The result: $1M in attributed pipeline and a 52x ROI.
Android 16 is now available on most supported Pixel devices. This release will be the only release in 2025 to include planned app-impacting behavior changes. There is another planned release for Q4 that will include new developer APIs, feature updates, optimizations, and bug fixes. The Android team plans to release updates quarterly. This post details some of the changes in Android 16, including changes to improve the consistency and visual appearance of apps, Android apps that adapt to any screen and window size, consistent progress notifications, and custom AGSL graphical effects.
Paws-on-MCP is a comprehensive Model Context Protocol (MCP) server that implements the latest specification. It demonstrates production-ready adherence to the MCP 2025-03-26 specification. Paws-on-MCP features HackerNews and GitHub API integrations with AI-powered analysis through advanced MCP sampling.
OpenAI started almost nine years ago with the goal of building the most impactful technology in human history: artificial general intelligence (AGI). The launch of ChatGPT on November 30, 2022, kicked off the current AI revolution. Over the past two years, the company had to build almost from scratch around this new technology, which was a difficult and messy process. Sam Altman considers these years to be the most rewarding, fun, best, interesting, exhausting, stressful, and unpleasant years of his life so far. He is confident that OpenAI now knows how to build AGI and believes that the first AI agents will join the workforce this year and materially change the output of companies.
Google has offered buyouts to employees across several of its divisions in an effort to reduce headcount. The 'voluntary exit program' applies to US-based employees. The buyout announcement comes along with a demand for employees to return to the office - workers who live within 50 miles of an office will be expected to assume a hybrid work schedule. Google has done multiple buyout offers in a few units this year.
Traffic for publishers is plummeting as chatbots are replacing Google searches.
It's possible to write CSS keyframe animations without specifying either a starting or ending point - this trick unlocks a capability within keyframe animations that makes them dynamic and composable.
OpenAI has slashed prices on o3 by 80% for both input and output tokens, making the model more accessible for developers seeking advanced reasoning capabilities.
Contracts are language, and large language models are exceptionally good at reviewing and creating them.
Apple appears to be retreating to safety and focusing on its core competencies.
OpenAI's o3-pro is very smart, but it needs a lot of context in order to work well.
and Richard Carrigan [23] for referring 5 friends to TLDR. Thanks for helping us spread the word! 🙏
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Ditch the IT bottleneck: AI agents are ready to deploy across departments. Think "collaborative playground" with invisible guardrails. Airia [4] lets every department build out their own use cases with security and governance baked-in: