B2B go-to-market teams are overloaded with tools but lack clear strategy, leading to stalled pipeline growth and ineffective systems. Many teams rely on fragile tech stacks patched together without orchestration, mistaking automation for progress. Most teams fail to define meaningful buyer signals and instead chase engagement metrics or generic intent data. AI tools alone won't drive pipeline without a cohesive, signal-first system. Marketing leaders must shift from campaign execution to GTM system design that spans product, sales, and client success.
Areas of focus include auditing the website, ghostwriting for founders 3-5x/week, and community building via newsletter swaps, co-branded content, and LinkedIn partnerships.
Brands like HBO Max, Samsung, and Amazon had ads placed next to AI-generated content that included deepfakes, misinformation, and copyright-adjacent animations.
JavaScript scope hoisting is an optimization used by bundlers to concatenate modules into a single scope instead of wrapping each in a function, but it breaks when combined with code splitting because it can't preserve the correct execution order of modules with side effects. This leads to different program behavior, with shared modules executing in the wrong order compared to unbundled code, affecting bundlers like Rollup, ESBuild, and others. The solution requires wrapping modules in functions to control execution order.
Go's `//go:nosplit` directive removes the usual stack overflow check from functions to improve performance. Nosplit functions skip the preemption check that normally compares the stack pointer against a limit and calls `runtime.morestack` when needed, making them about 2% faster in hot loops but potentially much faster when the goroutine struct isn't cached. However, nosplit functions are dangerous because they can cause stack overflows, so the Go linker includes safety checks to make sure chains of nosplit functions don't exceed a small stack limit (792 bytes).
A co-founder of Segment, which was acquired for $3.2B by Twilio, worked for OpenAI for a year. He liked the company's bias for action, its fast decision-making pace, its focus on practical AI safety, and its commitment to broadly distributing the benefits of AI. He played a key role in launching Codex, the coding agent, within an incredibly short timeframe.
To improve as a programmer, practice writing small, mental proofs to guarantee code correctness. Strive for code with high "proof-affinity," making it easy to reason about and verify. This gets easier with consistent practice.
Learning specific web frameworks like React may not be worth the time since they frequently change or become obsolete. Instead, focus on transferable fundamentals like vanilla JavaScript, strongly-typed languages, and understanding core specifications rather than framework-specific features like React hooks.
BNA UI is a beautiful and customizable UI component library for React Native. It has features like light/dark theme support, Expo Router integration, TypeScript support, and zero configuration setup.
Uzu is a high-performance inference engine for AI models on Apple Silicon that offers a simple API, hybrid GPU/MPSGraph architecture, unified model configurations, traceable computations, and bindings for Swift and CLI.
The `react-native-apple-llm` plugin enables React Native apps to use Apple's on-device Foundation Models for AI tasks. It has functionalities like checking model availability, configuring LLM sessions, and generating both structured JSON outputs and natural language text.
AI agents use LLMs to evaluate contexts, suggest and utilize tools to enrich those contexts, and manage flow control for tool usage. Customer support and bug triaging are good use case examples, and AI agents should be treated as software products requiring careful design, iteration, and human oversight.
"Asymmetry of verification" is where some tasks are much easier to verify than to solve, which is an important concept in improving AI. Examples include Sudoku, website operation, and BrowseComp problems, where easy verification enables AI training. The "Verifier's Law" states that AI's ability to solve a task is proportional to its verifiability.
GPUHammer demonstrates the first successful Rowhammer attack on GPU memory (GDDR6 in an NVIDIA A6000), enabling malicious users to induce bit flips, tamper with data, and degrade ML model accuracy in shared environments.
The curl bug bounty program has gotten a surge in low-quality vulnerability reports, many seemingly generated by AI, which wastes the security team's time and resources.
A misconfiguration in Cloudflare's systems caused a global outage of the 1.1.1.1 DNS Resolver service for about an hour on July 14 due to an error in managing service topologies.
This blog post explains the historical significance of ten "mostly dead" programming languages (COBOL, ALGOL, APL, BASIC, PL/I, SIMULA 67, Pascal, CLU, ML, and Smalltalk), highlighting their contributions to modern programming concepts and paradigms.
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A small group of members in Meta's newly formed superintelligence lab last week discussed the possibility of abandoning the company's most powerful open source AI model, Behemoth, in favor of developing a closed model. Meta has chosen to open source its AI models for years, with executives arguing that it is better for the technology to be public to accelerate AI development and make the technology more accessible to developers. A move to a closed AI model would be a philosophical change as much as a technical one. Meta has been delaying the release of its Behemoth model due to its poor internal performance.
Google plans to combine Android with ChromeOS. Chromebooks can already run many Android apps, and Android has been moving closer to ChromeOS with new features like desktop mode, resizable windows, and improved support for external displays. Bringing the two operating systems together makes sense as it will speed up feature development and improve functionality on tablets.
Israeli researchers have created an mRNA-based vaccine against Yersinia pestis, the bacterium that causes bubonic plague. The researchers hope the technology can be used to combat other lethal bacteria as well. When tested on animal models, the vaccine achieved 100% protection against pneumonic plague. The success of the study paves the way for a whole world of mRNA-based vaccines against other deadly bacteria.
The United States' Defense Advanced Research Projects Agency (DARPA) recently transferred over 800 watts of power over about 30 seconds with a laser beam across 8.6 kilometers. The estimated power efficiency was around 20%. The team used commercial ready-to-use solar cells placed within a receiver to turn the laser beam into electricity. Laser technologies are more suitable than infrared for building an airborne power relay network due to their high precision, long-range reach, and lighter and smaller equipment required to work.
Delve ran 4 ads 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.
AWS has introduced a new agentic IDE called Kiro that apparently avoids the pitfalls of vibe coding. It is built around a conversational interface that offers developers the chance to explain what they are trying to build. Kiro then uses generative AI to produce its response, which initially takes the form of a spec, not actual code. Kiro can handle multiple specs created by different teams that all work on different aspects of a project. It can use plugins written for VS Code and Open VSX.
Modern computing isn't possible without digital displays. The technology is underappreciated because most people have no idea how the technology works. This article covers the history of digital displays, how different types of displays work, what pixels are and why we use them, and much more. Understanding how a screen works unlocks a lot of understanding of how color works on digital displays, rasterization, GPUs, and shaders.
Meta plans to invest hundreds of billions of dollars into artificial intelligence compute infrastructure. It aims to bring its first supercluster online next year. Meta has been on a multibillion-dollar AI hiring spree in recent weeks. CEO Mark Zuckerberg reportedly grew frustrated with Meta's progress in AI, so he is revamping the company's approach to better compete with rivals like OpenAI and Google.
ByteDance is reportedly working on mixed reality goggles designed to layer digital objects over users' view of the real world to compete directly with Meta's upcoming mixed reality products. They will be built by ByteDance's Pico, the creators of the Pico 4 VR headset. Pico will keep the device lightweight by offloading most of the computing work to a puck connected to the goggles over a wire. Current Pico headsets aren't sold in the US, and ByteDance may face pushback over a US release due to its ownership of TikTok.
Gemini Space, which shows contextual cards on the lock screen and other places, currently only displays sports and birthday cards, but finance and Daily Hub features are expected in the future.
Despite their vast knowledge and high benchmark scores, no large language model has made a major breakthrough or unexpected insight - this post discusses a theoretical method for making models more insightful.
A person purchasing health insurance while on GLP-1 drugs may be assessed at the same level as someone at the same health level who isn't on the drug, but the person on GLP-1 is likely to return to their previous state of health within two years of stopping the medication.
Baseten recently outlined their multi-cloud capacity management (MCM) infrastructure for generative AI workloads. Baseten's MCM unifies 10+ clouds into a global GPU pool enabling infinite scaling and 99.99% uptime for generative AI workloads.
Cognition scooped up Windsurf's remaining 250-person team and $82 million ARR business after Google's $2.4 billion reverse-acquihire cherry-picked only the leadership, leaving employees behind without payouts. The acquisition gives Cognition both AI coding agents and IDE capabilities to compete with Cursor's $500 million ARR, and restores Windsurf's access to Claude models that Anthropic had cut off amid rumors of an OpenAI acquisition.
The newly formed superintelligence lab is considering abandoning its flagship open-source Behemoth model in favor of closed development, marking a potential philosophical shift from the company's long-standing commitment to open AI.
LLMs don't have background processes that allow the model to form connections between seemingly unrelated topics similar to how humans make new realizations while "daydreaming." This is the reason AIs have yet to make any new discoveries. This post proposes a remedy: a system that would prompt LLMs to randomly retrieve facts, generate novel connections between them, then use a critic model to filter for genuinely valuable insights.
Google acquired key members of Windsurf for $2.4 billion after OpenAI's $3 billion offer expired, while Cognition took over the remaining company. Despite Windsurf's impressive $82 million ARR and rapid growth, the loss of Anthropic API access and leadership exits weakened its market position. The AI coding industry's inflated valuations, driven by talent wars and platform dependencies, suggest Windsurf's sale price may have been below its potential value.
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Google's first Gemini Embedding text model is now generally available to developers in the Gemini API and Vertex AI. The model provides a unified cutting-edge experience across domains. It supports over a hundred languages and has a 2,048 maximum input token length. The Gemini Embedding model is priced at $0.15 per million input tokens.
Kiro is a Claude-powered "agentic IDE" that addresses the quality problems of AI-generated code by first producing specifications and user stories before generating actual code. The tool aims to move beyond "vibe coding" and reduce the time developers spend debugging and reviewing AI-generated code.
Energy-Based Transformers replace direct prediction with learned verification functions that assign compatibility scores between inputs and candidate outputs. The architecture is first to out-scale standard Transformers as it allows models to dynamically allocate computation and self-verify predictions without external supervision, achieving up to 35% higher scaling rates.