We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better: Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better: Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better: Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work! In summary: - As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding. - Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

“We are going to do a feature film on Baldwin: A Love Story, co-producing with Higher Ground.” @anoncontent President & CEO @darrenwalker announces a major new feature film adaptation live at #BloombergScreentime#. @HigherGroundMedia ⏯️

“We always think for every great macro transaction it’s usually the result of a thousand great micro ones.” @WWE's President Nick Khan shares with co-hosts of The Deal @jasonkellynews and @AROD how focusing on everyday execution creates the momentum needed for transformational enterprise growth. #BloombergScreentime# ⏯️

"We're controversial..." #BloombergScreentime# Host @Lucas_Shaw discusses @suno's controversial AI training methods, copyright infringement, and unauthorized artist likeness campaigns with @Suno Co-Founder & CEO @MikeyShulman. ⏯️ #BloombergScreentime#

"We're building not only models with those industry partners, but we're building products with those industry partners," @Suno Co-Founder & CEO @MikeyShulman, touches upon the co-creative process, which allows users to participate in music culture regardless of their status as an end user or artist. ⏯️ #BloombergScreentime#

"We let everyone make music. That includes grammy winners who are perfecting that last little bit, finding that last little bit of creativity in a song, and also grandmothers, who are making music for fun." @Suno Co-Founder & CEO @MikeyShulman ⏯️ #BloombergScreentime#

We criticized Lambda in ClusterMAX 2.0 for their reliability; in this round of testing, it was one of Lambda’s points of emphasis. Their passive health checks cover the relevant conditions and ultimately autoremediated three errors we simulated during testing. Two synthetic XIDs were autoremediated in less than 15 minutes, and there were connected dashboards to monitor node health. Our test that triggered a genuine XID 79 by performing a PCIe secondary bus reset brought the node into `NotReady` with no `GpuXid`, no cordon, and no monitoring visibility on the Kubernetes layer, but it ultimately rejoined the fleet after 2 hours. Our node-reboot tests on the Kubernetes layer also completed without incident. Great work by the Lambda team on the ClusterMAX Sliver!