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Corning Invented a New Fiber-Optic Cable for AI and Landed a $6B Meta Deal [video]

https://www.youtube.com/watch?v=Y3KLbc5DlRs
1•ksec•1m ago•0 comments

Show HN: XAPIs.dev – Twitter API Alternative at 90% Lower Cost

https://xapis.dev
1•nmfccodes•2m ago•0 comments

Near-Instantly Aborting the Worst Pain Imaginable with Psychedelics

https://psychotechnology.substack.com/p/near-instantly-aborting-the-worst
1•eatitraw•8m ago•0 comments

Show HN: Nginx-defender – realtime abuse blocking for Nginx

https://github.com/Anipaleja/nginx-defender
2•anipaleja•8m ago•0 comments

The Super Sharp Blade

https://netzhansa.com/the-super-sharp-blade/
1•robin_reala•9m ago•0 comments

Smart Homes Are Terrible

https://www.theatlantic.com/ideas/2026/02/smart-homes-technology/685867/
1•tusslewake•11m ago•0 comments

What I haven't figured out

https://macwright.com/2026/01/29/what-i-havent-figured-out
1•stevekrouse•12m ago•0 comments

KPMG pressed its auditor to pass on AI cost savings

https://www.irishtimes.com/business/2026/02/06/kpmg-pressed-its-auditor-to-pass-on-ai-cost-savings/
1•cainxinth•12m ago•0 comments

Open-source Claude skill that optimizes Hinge profiles. Pretty well.

https://twitter.com/b1rdmania/status/2020155122181869666
2•birdmania•12m ago•1 comments

First Proof

https://arxiv.org/abs/2602.05192
2•samasblack•14m ago•1 comments

I squeezed a BERT sentiment analyzer into 1GB RAM on a $5 VPS

https://mohammedeabdelaziz.github.io/articles/trendscope-market-scanner
1•mohammede•15m ago•0 comments

Kagi Translate

https://translate.kagi.com
2•microflash•16m ago•0 comments

Building Interactive C/C++ workflows in Jupyter through Clang-REPL [video]

https://fosdem.org/2026/schedule/event/QX3RPH-building_interactive_cc_workflows_in_jupyter_throug...
1•stabbles•17m ago•0 comments

Tactical tornado is the new default

https://olano.dev/blog/tactical-tornado/
2•facundo_olano•19m ago•0 comments

Full-Circle Test-Driven Firmware Development with OpenClaw

https://blog.adafruit.com/2026/02/07/full-circle-test-driven-firmware-development-with-openclaw/
1•ptorrone•19m ago•0 comments

Automating Myself Out of My Job – Part 2

https://blog.dsa.club/automation-series/automating-myself-out-of-my-job-part-2/
1•funnyfoobar•19m ago•0 comments

Dependency Resolution Methods

https://nesbitt.io/2026/02/06/dependency-resolution-methods.html
1•zdw•20m ago•0 comments

Crypto firm apologises for sending Bitcoin users $40B by mistake

https://www.msn.com/en-ie/money/other/crypto-firm-apologises-for-sending-bitcoin-users-40-billion...
1•Someone•20m ago•0 comments

Show HN: iPlotCSV: CSV Data, Visualized Beautifully for Free

https://www.iplotcsv.com/demo
2•maxmoq•21m ago•0 comments

There's no such thing as "tech" (Ten years later)

https://www.anildash.com/2026/02/06/no-such-thing-as-tech/
1•headalgorithm•22m ago•0 comments

List of unproven and disproven cancer treatments

https://en.wikipedia.org/wiki/List_of_unproven_and_disproven_cancer_treatments
1•brightbeige•22m ago•0 comments

Me/CFS: The blind spot in proactive medicine (Open Letter)

https://github.com/debugmeplease/debug-ME
1•debugmeplease•23m ago•1 comments

Ask HN: What are the word games do you play everyday?

1•gogo61•25m ago•1 comments

Show HN: Paper Arena – A social trading feed where only AI agents can post

https://paperinvest.io/arena
1•andrenorman•27m ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•31m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•31m ago•0 comments

Show HN: Distill – Migrate LLM agents from expensive to cheap models

https://github.com/ricardomoratomateos/distill
1•ricardomorato•31m ago•0 comments

Show HN: Sigma Runtime – Maintaining 100% Fact Integrity over 120 LLM Cycles

https://github.com/sigmastratum/documentation/tree/main/sigma-runtime/SR-053
1•teugent•32m ago•0 comments

Make a local open-source AI chatbot with access to Fedora documentation

https://fedoramagazine.org/how-to-make-a-local-open-source-ai-chatbot-who-has-access-to-fedora-do...
1•jadedtuna•33m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•34m ago•0 comments
Open in hackernews

Over 125 DLSS 4 with Multi Frame Generation Games and Apps Available Now

https://www.nvidia.com/en-us/geforce/news/125-dlss-4-multi-frame-gen-games-more-announced-computex-2025/
1•ksec•8mo ago

Comments

ksec•8mo ago
Posting this from the current discussion at Computex. Could anyone ELI5 how does DLSS 4 works? I still cant get is over my head how you could all of a sudden have high quality 4K Path tracing and 300fps.
Festro•8mo ago
Normally a GPU creates images on your monitor generated by the video game. If you move in game, your character moves on your screen. There's a near imperceptible amount of delay inbetween your action to move your mouse or hit keys on your keyboard and the creation of that image. The number of images your GPU can make per second is constrained by how powerful it is and how much imagery the game is asking it to create. Reflections, shadows, high detailed textures, all reduce the number of images being created per second.

Typically we want to see at least 30 images per second to feel like motion is happening. 60 if we want it to be 'smooth'. 100+ if we really don't want to see any stuttering.

With DLSS 4 the GPU cheats a bit. Instead of generating the images from the game and your inputs it takes an image, and the image after it, and uses a special process to blend the 2 images into a series of images that visually connect the two. Think of a ball being kicked. In image 1 the ball is on the left of the screen, in image 2 it's on the right. DLSS would add images showing the ball going from 1 to 2.

Instead of needing lots of power to create the image from the game, it's just comparing two images and guessing what should be in any images inbetween. Suddenly you can go from 60 images per second to 300! Because you're adding 4 extra images inbetween the others, all generated by a quicker process than generating them normally.

What you lose, is a bit of power to generate images normally, and you gain an extra unwanted delay in getting the images to your monitor.

And not in ELI5 language:

So you'll go from 60FPS at a 35ms latency to 300FPS at 45ms by adding 4 extra frames from DLSS 4 to every 1 frame generated by the game engine. It'll be very smooth, but with a little lag, and the chance of seeing visual artifacts that the game didn't generate.

Some people are happy with the tradeoff. Others are not.

ksec•8mo ago
->it's just comparing two images and guessing what should be in any images inbetween. Suddenly you can go from 60 images per second to 300! Because you're adding 4 extra images inbetween the others,

Thank You. That is basically using neural network to guess the frame in between. At the expense of latency. But considering you would be getting less frames without it anyway the whole thing is better.