35,595 results · Most relevant
Abhi Arya states that everything they did to fix the failure modes came down to one change: making uncertainty really legible. Failures should carry information — Reducto's Extract outputs confidence scores, bounding boxes, and information about what went wrong.
Dr. Elissa Epel says there are practices that help people feel ease with an uncertain future. Mindful check-ins — noticing that you are carrying around uncertainty stress — are one way. She suggests reframing uncertainty as the beauty of the mystery of life and the freedom of realizing you don't control tomorrow, and viewing things with curiosity and seeing what emerges. Her exercise: instead of an alert, forward-leaning posture of trying to predict the next second, lean back and take some slow breaths. Leaning back with slow breaths helps orient you and lets you 'face time' by letting it come to you and receiving what happens. The receptive posture is a completely different body stance than the usual daytime 'go mode'. She suggests declaring internally: 'I am in a receptive mode and I'm I
Dr. Elissa Epel explains that challenge-type thoughts ('I can do this, this is a great challenge and opportunity, I have what it takes') generate a healthier hemodynamic response: more cardiac output, better oxygenation to the brain, better problem solving. People who maintain a positive outlook and challenge response are able to maintain that positive outlook through the stressor. In lab studies, people showing the challenge response are less inflamed afterward — within an hour or two they didn't trigger the pro-inflammatory response. People with the challenge response tend to have longer telomeres, suggesting a slower speed of aging.
Andrew Huberman offers the exercise analogy: during a hard workout blood pressure, heart rate, stress hormones, and cortisol are way up, yet that sets in motion adaptations that bring you to a better place. Dr. Elissa Epel adds that short, repeated physical stressors like high-intensity interval training promote not just aerobic fitness but stress fitness. People who do short repeated physical stressors feel less rumination, less depression, and less anxiety — they tune up the nervous system. Repeated engagement with moderate stressors builds stress resilience when they are manageable — you become less threatened by them.
Dr. Elissa Epel describes a metaphor of pulling on a rope attached to a brick wall: trying to change the unchangeable only chafes your hands while the wall never moves. When you catch yourself trying to solve unsolvable problems, she recommends telling yourself 'drop the rope.' Dropping the rope frees your hands so you can live in the ways you do have control over, even though the brick wall remains.
Fedus explains why RL directly on live experiments (kick off an experiment, wait days, update on whether you found a room-temperature superconductor) is infeasible: rollout time, instrument queues, and furnace physics make variance reduction impossible with available agents. Instead, Periodic Labs constructs agents around the dataset the lab has already produced.
The guests describe the materials discovery loop as starting with figuring out what to make: assessing the stability of the atoms together and whether the material is expected to have the desired properties. The next step is figuring out how to synthesize it, which is non-trivial — even when a configuration is known to hold together, determining the processing conditions to realize it is highly non-trivial. They stress that a novel configuration of atoms is not the goal; the atoms must exhibit the property of interest when put together.
described as the lab's working model of discovery
Fedus describes the materials discovery loop in three stages: (1) decide what to make — a configuration of atoms that is stable and exhibits the desired property (not merely novel); (2) figure out how to synthesize it — processing conditions; (3) characterize what you actually made, since products don't come out labeled.
Nan Yu says the most successful efforts map agent design onto human nature, because people evolved to manage a limited number of parallel threads; managing 40 agents is too many for most people to keep up with — ask whether you could manage 40 direct employees.
Running backs are taught to run downhill (low and forward), which tends to give them higher backside mechanics; the objective when working with them is that they remain good football players, not that their running technique be changed. You should not make position players upright just for the sake of protecting hamstrings, because it would be detrimental to their game.
Dr. Morin explains that when running fast, good athletes have ground contact times around 100-150 milliseconds, so sprinters need not only a high level of strength in the ankle and foot, but also the ability to express that strength within a super short time window. Some athletes have high maximum strength (e.g., strong plantar flexion iso test) but still collapse at high speed because they only have strength when they have time to express it, while others who are not strong in the maximum strength sense can be super stiff and collapse less because they can produce force within 100-120 milliseconds.
Most of what E2B does is start from everything already running: with templates, you start your processes and they are already running when you come back to the sandbox. The approach is to start processes first and then save the disk state in RAM.
An E2B template is a snapshotted VM: start a VM, run processes, then save it as a template so others can resume where you left off. The workshop made roughly 200 copies of a template so every attendee starts where the presenter resumed.
Valuable skills are the rituals nobody wants rediscovered — knowledge that is not glamorous and deeply embedded in your company. Examples: the exact sequence of scripts and feature flags for a nice rollback, or the exact wording to use with a pesky enterprise customer about to churn. If agents try to rediscover this from scratch they will likely fail, and that failure can be really costly.
Installing community skills via npx without vetting installs prompt injections, root-requiring scripts, and someone else's API key alongside the skill; RunLayer scans thousands of skills daily and finds 'really weird stuff' inside.
The ten life elements most people call important are community, romance, parenting, family, recreation, friends, career, physical health, spiritual health, and personal growth; life is zero-sum with time, so an hour invested in one takes an hour from another, and assuming 12 focused hours a day you cannot give each element even an hour and 10 minutes.
The hour math is a hypothetical thought experiment.
Arik describes how trust in AI agents comes with time as users see the agent's precision. In Guitar's user base, users first see precise CI failure analyses uncovering actual bugs and set up rules to block on issues; then they try automated fixes and PR creation; seeing that precision, they unlock auto fix; they add rules to auto-approve PRs touching non-critical code or certain change types; and the next step is having the system unmerge and fix merge conflicts. Full autonomy doesn't come immediately; it comes with using the system and building trust that the agent is precise. When comfortable, users have set up enough rules and guardrails for full autonomy.
described
Goodwin explains that for iso-intelligence, making mixture-of-experts models sparser (from 1-in-16 to 1-in-128 or 1-in-256) saves a ton of flops. But when serving such sparser MoE models, today's HBM-based GPUs/XPUs become bandwidth-bottlenecked and serve the models at low MFU (flops utilization). As you scale the memory-bandwidth frontier, you get to conserve flops — reducing the flops used to reach a given level of intelligence, which multiplies global throughput.
numeric sparsity figures flagged as possible transcription errors
Liemandt argues that 80-85% accuracy on basic skills is not mastery and that students should nail the basics before moving to advanced material, using a sports analogy: a coach works on ball handling when a player loses the ball 20% of the time, rather than dunks and alley-oops.
Liemandt describes Bloom's famous 1980s Two Sigma finding: with an individual tutor to mastery level, kids can learn at two sigma (top 2%). He emphasizes that one sigma comes from the tutor and one from mastery, that mastery is the part everybody forgets (a non-mastery-based tutor won't get students to top 2%), that the claim assumes high levels of motivation, and that you need both individualized and mastery-level instruction to get that performance.
Choose sources → to get a library of your own and a daily brief.