It could also take $Trillions to make better EVs or solar panels or sneakers than China. Instead of spending $Trillions, just buy Chinese AI, and make them invest in US datacenters. The need for sectoral supremacy is objectively/purely for war against China “value”. This necessitates a skynet goal for military and information/population control supremacy. Neither skynet nor war on China will make your (non corrupt insider) life better.
This is needed for all the 0 negotiation BS between reopening somewhere between any day in last 2 months and labour day, and just letting Israel supremacists derail any reopening of SoH.
It’s treasonous corruption that steals too much of our money for their privatized profits that need to be nationalized, in similar confiscation proposal. Amtrak/rail doesn’t steal excessive public money or elect corrupt leaders. Nationalizing libraries or transportation doesn’t necessarily fund it more. Nationilazing corrupt evil is path to control lobbying for the supremacism of evil.
it actually creates symetry for risk/reward, but it does incentivize giving skynet contracts with argument that people get 50% of the proceeds from skynet abuse.
Defense, oil, and media industries should be a higher percentage. They are historically responsible for most corrupt lobbying/disinformation/warmongering and alliance with zionazi rule over the US. The strategic unanimity of “must beat China or maintain zionazi bias over population control” for AI means that it is meant to be a corruption vector for skynet, funneling all of our wealth and liberty onto privatized profit from skynet.
It all depends on how this is funded, and this is mostly a colonization trap for Iran. US has recently controlled the budgets of Afghanistan, Iraq, and now Venezuela. There is full threat of confiscation for any non-compliance, and this was done to Afghanistan.
Funding could be extorted from GCC colonies, and like Venezuela, pressure for US major oil companies. There is zero history of any US investment in these colonial trap arrangements. Just bribery of political class to keep US control as long as feasible. Like Venezuela (and Iraq), US oil companies would be reluctant to spend cash because future nationalization is a likely retaliation to US extortion.
top 11 hottest are 11 years since 2015. Top 3 are last 3.
there were 23 and 24 records set. 25 was 3rd warmest year. Every year since 2015 is in the top all time list. I get the point that el nino will break record this or next year. But progression has bigger consequences than this headline.
Very difficult project to track data for. Major difficulty is that capex budgets are like share buyback budgets. Implementation speed subject to change. It’s hard to measure revenue/profitability because AI credits tend to be bonus perks for enterprise customers, and in Meta’s case they use it for better brainwashing/ad revenue.
The best way to measure Bubbliciousness is trends in spot GPU rentals. Nvidia has been selling more datacenter GPUs than datacenters completion for over 1 year. Those GPUs filter down to tier 2 providers because they cost $1.30 to $2.70 per hour to just sit in a warehouse. Anthropic’s deal to replace grok at Colossus 1 has significantly reduced tier 2 provider usage, and those spot rates have collapsed below their runcosts. https://lemmy.ca/comment/23443450
it’s important that dogs be armed. Only a good dog with a gun can stop Kristi Noem.
It’s much more likely to be like internet fiber. Some was needed/used.
datacenters will always leverage scale, and AI is only economic at 16+ concurrent users. delivers 3x the tokens/s of a single user. Current rental rates for H200s are below their runcosts. Capacity is already too high in US. Innovations for smaller, faster, cheaper models are providing significant value for less hardware. Gemini flash 3.5 is very small and fast, at much lower cost as top 2 US labs. Deepseek v4 has massive cost reductions that will filter down to rest on industry, especially for context compression which is what allows more users on a single GPU cluster. Qwen 3.6 does bring size down enough to run 3-4 month old state of the art models on consumer hardware, but again multi user service at (pro instead of industrial) 96gb ram.
MTP and Turboquant are other technologies that increase tps delivery at less ram. Software stacks making better use of GPUs is eating token demand growth by itself even as exaggerated capacity comes online at slower pace than hardware investment values justified.
I’d love for these politicians to explain to me how age verification of Linux web servers should work for auto-scaling environments where instances are spun up and terminated automatically based on traffic volume.
Come on, can’t be that tedious. What could it be 200-300 instances tops per day? My kid sister does that many selfies.
they do have more successful dance shows too.
Atlantic doesn’t want what’s best for you anymore than Netanyahu. This is best outcome, and it’s already taking too long.
They need access to your phone to sideload their spyware?
I would doubt this. I’d especially doubt that a winning campaign would be to promise to give all KY electricitity to a datacenter. AIPAC did make a victory tweet. I didn’t see campaigns, but I doubt it was focused on who loves AI the most.
Even if you like all 3 of the other things, it doesn’t mean you need it in gaming. It’s not as though porn thinks it needs to blend in other attention competitions. A lot of games have math overlap. Gambling is for conning people bad at math.
In summary, this all seems like bad directions.
for Massey, this was mostly AIPAC money even more than they spent on previous primaries to defeat Cori Bush. The playbook for successful APAIC operation is to never mention Israel. Just smear opponent. Not sure how Massey primary was conducted, though.
taps ctrl and shift repeatedly.
this is the nature of this flame war. Perfect replication of the end result, which is extremely opaque in how it works, is not nearly as important as the weights, that you can post train for any domain specific/general improvement with any other dataset. Which is how the authors would improve/change the weights further as well.