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A guide circulating on AI usage identifies five practical adjustments users can make to improve their results with tools like ChatGPT and Claude, including writing better prompts and making smarter use of memory features. It frames the gap between users who find AI tools highly useful and those who don't as largely a matter of technique rather than the tools themselves.
An Entrepreneur contributor whose company teaches AI for business argues that people should build saved, reusable AI prompts instead of rewriting instructions from scratch each day. The piece outlines a method where users have an AI interview them one question at a time about their role, workflow and expectations, then generate copy-ready prompt instructions for recurring tasks.
Wonder Tools, a newsletter covering useful apps and sites, published a roundup of five techniques for overcoming writer's block. The suggestions include using dictation apps, running timed writing sprints, and applying AI-generated prompts to get past a blank page.
Proofs and Prompts has compiled a running thread of mathematician reactions to OpenAI's 6 October announcement that its models produced solutions to over 100 research-level math problems, including one described as resembling a Quasi-Riemann result. Contributors like Tim Santens and Roman Sauer describe being stunned that the models applied known but obscure techniques across very different problems, and the site says it will keep collecting reactions for another week.
A recent gathering of innovative startups supported by Convergent Research highlighted the positive outlook among mathematicians regarding AI's influence. While acknowledging significant changes to traditional workflows, many see potential for AI to complement and enhance mathematical research. The discussion reflects a community adapting to rapid technological advancements that challenge conventional problem-solving methods.
Meshy is promoting its Meshy 7 AI platform, which converts text prompts or 2D images into print-ready 3D models without manual modeling. New customers can get 60% off their first month's subscription using the code TOMESHY60, applicable to paid tiers above the free plan.
A commentator argues that instead of obsessing over crafting the perfect text prompts for LLMs, developers should build interlocking evaluation and optimization pipelines that use additional AI systems to manage and refine model behavior. The piece contends that treating prompts as meaningful language leads people to mistakenly attribute intent or consciousness to systems that have neither.
A new essay from Proofs and Prompts traces how AI systems went from struggling with basic arithmetic three years ago to earning IMO gold-medal-level scores last year, and are now autonomously cracking open research problems. The author, who previously gave a talk called 'The End of Mathematics,' argues this trajectory will force a fundamental restructuring of how the mathematics profession operates, even though outright 'solving' math isn't the point.
Meta says it has fixed a Meta AI feature that generated invasive automatic prompts on Instagram posts, such as questions identifying a poster's child or home location, after parenting blogger Kalie Robins showed the tool piecing together private details from years of old photos and family accounts. Meta confirmed the feature missed its intended purpose and will no longer surface such personal suggestions, though it gave few specifics on what exactly was changed.
Kage is a new tool that lets users submit a website URL, which it then captures and analyzes for design elements. After review, the site's design patterns are added to a searchable library that can be converted into prompts for AI design agents.
A new essay contends that the main obstacle to wider AI adoption isn't the technology's power but users' inability to know what to ask for. It compares this to Alan Kay's ant-in-the-canyon metaphor: skilled users see a full landscape of possible automations, while everyday users face a blank prompt with no sense of what's achievable.
Security researchers found that attackers can embed HTML invisible to human readers—such as white-on-white text or zero-size fonts—inside emails. When an AI-powered summarizer processes the message, it reads this hidden text as legitimate content and can produce a summary containing false or malicious instructions for the recipient.