Teachers provide a subject, grade, and topic, and Gemini generates a web-based simulation with staged levels, hints, and feedback; only 3.5% pass all checks on the first try, reaching 69.3% after 10 rounds of self-correction. Student learning gains data is not yet available.
Each thread is an independent cloud Claude Code session running on its own branch; Claude in the project conversation handles dispatch and tracking, queuing blocked items under Waiting on you. Currently in rolling public beta for Pro and Max users.
Evaluations form the foundation: fix retrieval and context first, tune system architecture next, and only then consider training models. Spanning error analysis, model cascades, multi-vector retrieval, OCR selection, inference latency, Agent sandboxes, and post-training, these 13 talks deliver actionable methodologies backed by empirical measurements.
OpenAI breaks down usage, task, and Codex contribution analytics in the ChatGPT Admin Console, and how to partner with business leads to set baselines, track outcomes, and estimate ROI. Includes a sales research example you can recalculate using your team's own assumptions.
When frontier models make mistakes, it is usually because they misjudged your goals and tradeoffs. Spell out your goals, your constraints, and where you are willing to give ground, and the model can help you find a better approach. Includes a real prompt and a breakdown of it.
From generating buzz, building launch momentum, and word-of-mouth distribution to conversion, competition, pricing, and retention: testable growth tactics filtered by objective, effort, and cost.
A complete catalog of 43 workflows and skills, a week-by-week automation cadence, 37 existing connectors, and five business case studies—with a clear note that Anthropic has not published the full list of 27 newly added integrations.
Codex has shifted the basic unit of work from line-by-line coding to goal delegation, pushing bottlenecks downstream to CI, review, deployment, and operations. This explainer examines the evidence, human checkpoints, and future automation directions of OpenAI’s nine-step software factory.
FDE fits products that are technically complex and serve customers without the engineering capacity to implement them; if every customer requires a fresh build, the team quickly becomes a dev shop.
AIforce is a dynamic interaction layer connecting Salesforce data, business semantics, permissions, and agents with various AI interfaces, allowing employees to invoke and execute enterprise capabilities in their current work environments without entering a fixed backend.
Gemini 3.8 Live targets low-latency deployment at scale, while Extended Thinking handles complex multi-step reasoning. This explainer gives the per-minute price, benchmark results versus the previous generation, seven bilingual demos, and Live API setup instructions.
Diogo Almeida, who co-invented ChatGPT and RLHF at OpenAI, has launched the System One model paradigm and its first public model, Jev: it generates no free text, returning probabilistic decisions only within code-predefined structures.
Why an AI software engineer must have a Mac, and how Cognition connects the closed loop of native application runtime verification across storage, networking, image preparation, live video, and the accessibility tree.
General-purpose LLMs performing query fan-out easily fall into synonymous repetition and suffer from token-by-token generation latency. R4T shifts set-level policy exploration to offline training, handing execution over to a lightweight diffusion retriever for parallel generation.
Josh Elman draws on his firsthand experience at LinkedIn and Twitter to show that while AI has inverted the development cycle, it has not decided what is worth building for teams; what product managers truly deliver is a shared story that is understandable, repeatable, and verifiable by user behavior.
Claude Fable 5.1 used adjacent text within the book to solve 64 numbers and advanced a larger 285-number cipher down to just nine unknown letters. What is truly worth understanding is how it selected verifiable problems, found indexing rules, and where it stopped.
MIT connects 8 principles, 4 course-policy templates, and 26 actions into an iterative redesign of learning goals, assessment, residential community, and continuous governance.
Provide your data and use case, and AI can select from editorial narrative charts, basics, animated charts, maps, and large interactive graphics to generate ready-to-open HTML charts or full-page reports.
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