Asana used OpenAI Codex to replace an outdated testing system in two weeks, with about $12K in model and infrastructure costs.
Asana leveraged OpenAI Codex to overhaul an antiquated testing system, accomplishing in just two weeks what had previously required five years of engineering effort. The project cost approximately $12,000, demonstrating a rapid and cost-effective solution to a long-standing technical challenge.
GPT‑6 Astra is a new OpenAI model rolling out today to a limited set of organizations and soon to all ChatGPT Plus, Pro, Business, Enterprise users, and via the OpenAI API and AWS. It is priced at $10/million input and $50/million output, matching Claude Fable 5/5.1, and outperforms Fable on most OpenAI self‑reported benchmarks, achieving 99.9% on the ARC‑AGI 3 benchmark with a custom Provider Adapter harness. Astra excels in security tasks—scoring 100% on ExploitBench, 42.4% on ExploitGym, and 99.2% on SRE‑Bench—and handles long context well, hitting 100% on OpenAI’s eight‑needle benchmark at 256K–512K tokens and 96.3% at 512K–1M tokens, though it remains behind Fable on the Intelligence Index and Meta’s Muse Spark 1.3.
Why this matters less for what Astra can do and more for what every other model hasn't been tested for
The post GPT-6 Astra Just Hit OpenAI's Highest Cybersecurity Risk Level appeared first on Towards...
By Benjamin Nweke
The article titled "How to Maximize GPT-6 Astra" shares the author’s first impressions of OpenAI’s new frontier model. It discusses initial experiences and observations with GPT-6 Astra, offering insights into its capabilities and potential applications. The post was originally published on Towards Data Science.
By Eivind Kjosbakken
Fine-Tuning GPT-4o Webinar