Ron. P @RonP097

@AskKubeir Better late than never! I have so many friends in my circle who did the same started payroll to have the CEC experience did that for a year or two and they all got the ITA and got PR approved.

@GemsOfRailway Typical same scene

@AskKubeir You are doing great! With these information people should know what all steps to take plan etc. Instead they try to reassure that nothing will happen and keep giving false self hope instead of facing reality! If system will change / not people will keep getting ITA achieve PR.

@Sahilkr11_ LoL she’s wearing the gloves but still touching the food with her other bare hand! What an interesting High Level IQ

@INTERIORPORN1 @grok are pet in cabin allowed in this ? If you are paying 14k $ ??

@AskKubeir I guess the median wage scale is the main problem due to its skewed data! Its reference points is 2022-2023 post covid bubble and AI race! Also be it junior or senior both are treated at same level so meeting the median is not feasible unless 6/7 yrs of experience works!

@AskKubeir @AskKubeir What if we are earning like $70k and above i.e 40$ and above hourly. But the median wage remains below the job bank median wage required for the NOC code so does it means we cant apply for OINP right ?

@KanwarSierah Does this mean that these 33k is separate from Express Entry and won’t be counted toward the Federal Target ?

@AvatarMovie2026 @xdownloaderbot download it

A Waterloo undergrad just built the first working implementation of Google's most disruptive AI paper. In one week. Memory stocks crashed. Investors got it exactly backwards. TurboQuant compresses the KV cache — the part of an AI model that eats your GPU memory during long conversations — from 16 bits down to 3 bits per value. 5x compression. Near-zero quality loss. No retraining needed. Drop it into any existing model and it just works. Micron, SK Hynix, Samsung, SanDisk all dumped 3-6% in a single day. Wall Street's logic: if AI needs less memory, sell memory stocks. That logic has been wrong every single time in the history of computing. This is Jevons paradox — the 160-year-old principle that says when you make a resource more efficient, you don't use less of it. You use more. Coal engines got efficient, coal consumption exploded. Bandwidth got cheaper, data consumption went vertical. Storage got dense, we filled it with 4K video. Every time. Here's what TurboQuant actually does to demand. A 70B parameter model that used to need a $10,000 workstation to run at long context? Now runs on a $1,500 consumer GPU. A model that choked at 32K tokens? Now handles 100K+. A smartphone that could barely run a 3B toy model? Now runs 7-13B with thousands of tokens of usable context. You didn't reduce demand. You just made AI accessible to a billion more devices. Every one of those devices now needs memory. Every user who couldn't run local AI before now can — and will. And every developer who hits the new ceiling will immediately ask for more. Anirudh BV — a student at UWaterloo — took Google's paper, wrote 2,000 lines of CUDA, and had it running on Nvidia's Blackwell B200 within a week. From pseudocode to live generation from compressed memory. If a college kid can ship this before most corporate labs, the adoption curve isn't years out. It's already here. The investors who sold memory stocks on this news will be buying them back within two quarters. Efficiency doesn't kill demand. It creates the demand that didn't exist yet.

keyboard_arrow_left Previous keyboard_arrow_right Next

ani @anirudhbv_ce

6 months ago

I implemented @GoogleResearch's TurboQuant as a CUDA-native compression engine on Blackwell B200. 5x KV cache compression on Qwen 2.5-1.5B, near-loseless attention scores, generating live from compressed memory. 5 custom cuTile CUDA kernels ft: - fused attention (with QJL

145 310 3K 814K 3K

I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue. There's a new programmable layer of abstraction to master (in addition to the usual layers below) involving agents, subagents, their prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP, slash commands, workflows, IDE integrations, and a need to build an all-encompassing mental model for strengths and pitfalls of fundamentally stochastic, fallible, unintelligible and changing entities suddenly intermingled with what used to be good old fashioned engineering. Clearly some powerful alien tool was handed around except it comes with no manual and everyone has to figure out how to hold it and operate it, while the resulting magnitude 9 earthquake is rocking the profession. Roll up your sleeves to not fall behind.

@Rainmaker1973 Such an amazing creature !! It made me remember this moment from Attack on Titan.

In hindsight the importance of GPUs for AI was something we really got right!

illiquid @lefttailguy

11 months ago

NVIDIA $5T today, but the writing has been on the wall Since @AndrewYNg and team published this paper in 2009. Were there any large/notable hedge funds that actually nailed the NVIDIA trade early? Say 2016/2017? There was ALOT of writing on the wall at that point, and company

23 23 248 317K 119

You can now track insider trading on Perplexity Finance. We will be adding politician trading shortly.

"You only get to die for having lived" hits hard everytime

code is the source of truth

@_self_healing 24:24

@systemdesignone Leetcode

@NoahEpstein_ Vault