But he would try to be out of the house a ton. He was doing the bare minimum at home. That’s when I realized how much I was doing anyways. I miss the income and another adult to share the workload around the house, but I don’t miss him.

🚨 Alisson Becker: “Missing games for Liverpool was part of the plan to make sure I was ready for the World Cup.” 👀 Liverpool fans, what's your reaction to this? 🤔👇 👍 Smart workload management 👎 Club should always come first #LFC #Alisson #WorldCup #BallTalkHQ

Balancing idle capacity dynamically can improve efficiency by distributing workload more evenly across available resources

weekend @evo__hq activities: given the recent sovereign-AI narrative (amidst anthropic's fable pullback), i wanted to see if evo could help make some of the indian models we have better in whatever way. so i kicked off an autoresearch run on evo to see if @SarvamAI's 30B decode throughput could be improved, at bf16, on a single H100. currently 10 hours in. so far, evo seems to have found ~3% improvement. the metric is geometric mean tok/s across batch sizes 64 / 128 / 256, measuring steady-state decode only. prefill is timed out, so this is purely per-token decode rate on a fixed workload. evo also ensures that anything that got faster by changing outputs, lowering precision, or messing with MoE routing was rejected by the accuracy gate. the gate compares each candidate against a frozen baseline on both next-token distributions and actual decoded tokens. if argmax agreement or logprob drift moves meaningfully, the change is rejected, even if it is faster. very imp caveat: these are experiment-harness numbers, not production serving numbers. the gain still needs to be validated in a real serving setup before anyone treats it as real capacity. i also havent done an external audit for any benchmark hack the agent may have done. a potential ~3% bump is a potentially a pretty significant improvement for someone like sarvam at that scale. decode is a major part of inference cost. a ~3% decode-side throughput gain at identical accuracy means more capacity, or fewer GPUs, without changing the model. i also want to s/o to @vishnuvig of jarvislabs.ai / @e2enetworks for compute support. i am trying to use more and more compute from indian providers as much as i can and give feedback to improve the experience as well

The Rico case is undeniably won, federally! I'm just trying to collect from the state case! Imma a workload beast!

Best for what: coding, long-context research, or cheap high-volume inference? The ranking usually changes once you factor tool-use reliability, latency, and token economics. "Best OSS model" without a workload is mostly benchmark cosplay.

I don't think it is caused by anything mentioned. I put blame on high living costs, unavailability of housing, childrearing facilities and heavy workload on people.

...with absurd impact on both ends. Then the playoffs arrive, rotations shorten, his workload increases, and he struggles much more. Again, it's like 2024 LAL vs DEN. LAL starts were always better, but LBJ and AD couldn't arrive mentally fresh and ready in the 4Q.

#yumetwt 2026 c🩷mmissions are finally open, please read everything thoroughly. My slots vary based on workload #commissions #commissionsopen

Workload routing to the right model for the right job & token cost is the future.

1. You're not tracking your calories correctly/underestimating it. No way you eat 2,2k kcal, doing all that and still gaining. 2. You're exaggerating your workload/step count. 3. Some strange disease. 4. flat out lying. Which I hope is not. That would be sad.

Unfortunately, it was a very difficult and therefore disastrous weekend 😞. The last positions were expected, but the retirements mean the workload needs to be even heavier. We eagerly await the arrival of the upgrades 🤞

Public school enrollment dropped another 5% last year. Teachers are not providing a quality education and parents are moving their children elsewhere. What additional workload or expectations will teachers have that justify additional pay they are asking for?

still waiting for a real workload outside testnet tbh

Every color has a purpose. Designed to reduce workload during one of the most demanding phases of flight, every indication serves a function—nothing is purely decorative. A true aviation instrument, engineered for clarity when it matters most. #AlpinaWatches #SwissMade

Burnout recovery is often framed as an individual responsibility. Rest matters. Boundaries matter. Recovery practices matter. But organizations must also examine the conditions that created or intensified burnout in the first place. Psychological safety plays an important role. When employees feel unsafe, they may hide exhaustion, avoid asking for help, and continue performing capacity they no longer have. In my upcoming book: Psychological Safety at Work: Through the Lens of Industrial/Organizational (I/O) Psychology, An Approach to Trust, Learning, and Organizational Performance, I discuss how psychologically unsafe environments can intensify burnout by adding interpersonal risk to already demanding work. Recovery requires more than encouraging self-care. It requires creating climates where employees can speak honestly about workload, strain, and support needs. Sustainable performance depends on whether organizations can detect human limits before those limits become breakdowns. A critical question is: Are employees safe enough to tell the truth about their capacity? #Burnout #PsychologicalSafety #EmployeeWellbeing #Leadership

Decreasing your workload but increasing mine--happily I must say. I'll have to review my manual on twin yoke abnormalities.

Around past 2pm wish the day could come to an end faster and the workload is unusual at that time

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