frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

Book of American Types – ATF Standard Faces, 1934

https://archive.org/details/ATFBookOfAmericanTypes1934
1•everybodyknows•2m ago•0 comments

Australia toughens social media ban, doubles potential penalties for tech firms

https://www.reuters.com/business/media-telecom/australia-toughens-kids-social-media-ban-doubles-p...
1•1vuio0pswjnm7•4m ago•0 comments

'The cult of Elon': SpaceX investors grapple with volatility amid big swings

https://www.cnbc.com/2026/06/26/spacex-volatility.html
1•1vuio0pswjnm7•5m ago•0 comments

Low dose Naltrexone [video][9 mins]

https://www.youtube.com/watch?v=S5Y_ShsPTpQ
1•Bender•6m ago•0 comments

Billionaire Jeremy Grantham says Bitcoin will 'dwindle away with a whimper'

https://www.cnbc.com/2026/06/26/billionaire-investor-jeremy-grantham-says-bitcoin-will-dwindle-aw...
3•1vuio0pswjnm7•6m ago•0 comments

David Sedaris on his Duolingo obsession

https://www.theguardian.com/books/2026/jun/28/david-sedaris-duolingo-obsession-the-land-and-its-p...
1•andsoitis•9m ago•0 comments

Nostalgia – it's not like it used to be (2012)

https://www.bbc.com/news/magazine-20726824
1•ryandrake•19m ago•0 comments

Clean Code: Second Edition Critique

https://bugzmanov.github.io/cleancode-critique/clean_code_second_edition_review.html
1•bmacho•20m ago•0 comments

The church members disagree on politics. Together theyre wiping out medical debt

https://www.npr.org/2026/06/28/nx-s1-5847966/medical-debt-politics-republican-democrat
1•Jimmc414•21m ago•0 comments

Memory Safe Context Switches

https://fil-c.org/context_switches
1•pizlonator•23m ago•0 comments

Tailwind

https://www.kevinsdias.com/posts/tailwind.html
1•diasks2•23m ago•0 comments

The Hunt for the Death Valley Germans

https://otherhand.org/home-page/search-and-rescue/the-hunt-for-the-death-valley-germans/
1•signa11•24m ago•0 comments

Consistency, but in Excellence Not Appearance – Jim Nielsen's Blog

https://blog.jim-nielsen.com/2026/a-consistency-of-excellence/
1•tambourine_man•25m ago•0 comments

Blink If You're Human

https://dynomight.net/blink/
1•Curiositry•27m ago•0 comments

Polymarket traders revolted over one silly sillable

https://www.nytimes.com/2026/06/28/business/donk-polymarket-prediction-markets.html
3•croemer•28m ago•0 comments

Show HN: I Made a WebGPU Based Agent/Worlflow Explainer

https://tdu-naifen.github.io/AgentVisualization/
1•milkpowder101•32m ago•0 comments

The oracle problem is three thousand years old

https://pilgrima.ge/p/the-oracle-problem
2•momentmaker•33m ago•0 comments

Collider: A meson package manager – A hash proves the bytes, not the source

https://collider.ee/blog/2026-06-28-1500_a_hash_proves_the_bytes_not_the_source/https://collider....
1•mog_dev•33m ago•0 comments

The only CLI for browser agents

https://fuckui.com/fuckui
1•keepamovin•33m ago•0 comments

Anthropic Claude Fable 5, on track to return soon (possibly this week)

https://www.axios.com/2026/06/27/anthropic-fable-5-return-soon
3•dlg•35m ago•0 comments

Token Entanglement in Subliminal Learning

https://owls.baulab.info/
1•derbOac•38m ago•0 comments

Why it's almost impossible to produce a smartphone in the United States

https://www.neowin.net/opinions/why-its-almost-impossible-to-produce-a-smartphone-in-the-united-s...
1•bundie•47m ago•0 comments

Signed satellite images for AI agents

1•avijeetsingh16•47m ago•0 comments

Zero Interest Rate Tech Debt

https://twitter.com/staysaasy/status/2071312293326172647
2•thisismytest•56m ago•0 comments

Google: An 8-minute step-by-step guide to building the smallest Agent loop

https://twitter.com/Easycompany333/status/2071204465168769451
4•aurenvale•1h ago•2 comments

Show HN: SaaS landing page template (React/Vue/HTML, Tailwind), free and MIT

https://github.com/hannah-wright/saas-landing-page-template
1•hannahwright•1h ago•0 comments

Tell Congress: Don't Force Age Checks Online

https://act.eff.org/action/tell-congress-don-t-force-age-checks-online
7•rmason•1h ago•0 comments

HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88

https://danunparsed.com/p/hackerrank-open-source-ats
2•sambellll•1h ago•0 comments

AI and Liability

https://www.schneier.com/blog/archives/2026/06/ai-and-liability.html
3•lwhsiao•1h ago•1 comments

AI-assisted binary patching to fix an abandoned router's DHCP bug

https://gurulabs.com/blogs/edgeos-dhcrelay-binary-patch/
2•4onthefloor124•1h ago•0 comments
Open in hackernews

Sophon PFG-1: a monolithic-3D AI ASIC with 330 GB of on-die DRAM and no HBM

https://www.phantafield.com/whitepaper
24•minkowsky•1h ago

Comments

codingpanic•1h ago
I've been wondering how long before RAM is fabbed on die to get around supply issues. This is one of the first I've read of so far. How long before Apple releases a CPU with ram on die?
minkowsky•1h ago
Author here. The supply angle is exactly the motivation — HBM is the hardest part to get and ~26% of an AI rack's BOM.

First, separate three things people lump together. Apple already does memory on package (M-series unified memory = LPDDR5X dies next to the SoC). The near-term industry path is bonded stacking (AMD 3D V-cache, HBM4's logic base die). What we're doing is monolithic — growing the memory on top of finished logic. Three reasons that distinction matters:

1. Bonding only helps at the margin. A hybrid-bond interface still carries a relatively large interconnect capacitance in um scale, so at memory bandwidth the I/O drivers crossing it dissipate most of the power and overheat — you move the memory closer without escaping the I/O energy. Monolithic inter-tier vias are nano-scale (we model ~1% the interconnect energy of a bonded interface), and that's the only thing that actually moves the needle.

2. 2D-TMDs are the only functional CMOS you can build in the BEOL. Monolithic 3D means fabricating the upper tiers after the logic, at ≤450 °C, or you cook everything underneath. Silicon needs ~1000 °C; low-temp oxide semiconductors (IGZO) are n-type only, so no real CMOS. 2D-TMDs give both n- and p-type at BEOL temperature. Nothing else does.

3. ~6 orders of magnitude lower off-current (~1 fA/µm) finally makes a capacitor-free cell work. Conventional 1T1C DRAM needs a big storage capacitor — the deep-trench / high-aspect-ratio etch you can't do in the BEOL anyway. A 2T0C gain cell holds charge on a transistor gate with no capacitor; in silicon it leaked away in microseconds, so it was never usable. With 2D-TMD leakage you get ~1.8 s retention — refresh at ~1 Hz and drop the capacitor, and the trench, entirely.

Rohansi•52m ago
They're typically manufactured with very different processes so one has to wonder what compromises are being made here to get both on the same die.
wmf•1h ago
This design is absolutely wild. It probably won't work but I admire the dream.
minkowsky•1h ago
Author here. The economy is more realistic than the wafer-scale ASIC by Cerebras.
binyu•1h ago
Hello, kudos for the tremendous work. Could you explain the difference between your design and Cerebras?

Bests

minkowsky•59m ago
Author here. Thanks! Short version: Cerebras and we are attacking the same memory wall from opposite axes — they scale out in 2D, we scale up in 3D.

Cerebras WSE-3 is a brilliant packaging play: one wafer-scale chip (~46,000 mm², ~900k cores) with ~44 GB of SRAM spread across the plane, so compute and memory sit side by side with enormous bandwidth. The catch is density — SRAM is a 6T cell, so even a whole wafer only holds ~44 GB. An 80B model doesn't fit on-wafer, so weights stream in from external MemoryX (off-wafer DRAM). It's fast, but it's a ~23 kW, multi-million-dollar system, and large models are still memory-streamed.

Sophon is a single ~750 mm² die. Instead of spreading SRAM across a wafer, we stack DRAM on top of the logic — 64 monolithic 3D tiers of 2D-TMD compute-in-memory and capacitor-less gain-cell DRAM. The gain cell is denser than SRAM per layer, and we stack 32 memory tiers of it, so we get 330 GB on one normal-size die — enough that an 80B model is fully resident, no streaming, no off-chip memory at all. ~1 kW, not 23 kW.

So the real difference is SRAM-in-2D vs DRAM-in-3D: Cerebras maxes out planar SRAM area; we trade to denser DRAM and stack it vertically, which is what buys GB-scale on-die capacity.

Honest caveat: Cerebras ships real silicon today and is genuinely fast — they proved wafer-scale integration works. We're pre-silicon, betting on a harder materials path (2D-TMD monolithic 3D). The upside, if it yields, is capacity-per-watt and per-dollar that planar SRAM can't reach.

addaon•59m ago
Since when are we doing 32-layer planar transistor logic on a single chip? Even ignore the use of FETs for eDRAM… I didn’t realize we had decent logic density possible on BEOL.
brcmthrowaway•57m ago
What is this? AI generated company?
vessenes•53m ago
Minkowsky, cool design! Question - the ASIC designers I've worked with over the years have been fairly adamant that integrating memory on package interspersed with logic is very difficult; the general statements run like "those designs always look great on paper, but never tape out properly".

Have you done any hardware tests of this plan? Is this still considered quality advice?

Second q, why start with 28nm? Is the idea that you want to stick with TSMC and be able to shrink? If this does in fact work well, I can imagine wanting to shoot for a smaller process node pretty quickly. Is there some sort of tech / design gap you'll need to figure out as you go?

gfody•44m ago
isn't cerebras the pudding proof of this design? it seems like ai chips galore are appearing from the woodwork but cerebras is 10 years down this rabbit hole and poised to dominate
minkowsky•21m ago
Due to the thermal budget, most of the silicon design is constrained to a 2D layout. So the Memory is competing with logic for layout. Now we stack logic in the backend between metals.

We fabricated 2T0C DRAM arrays with a 3D monolithic structure. That's a must-do.

Why 28nm? Because it's cheap, widely available, and already gives us enough performance to beat Nvidia Vera Rubin. We have a road map, scaling it down. https://www.phantafield.com/whitepaper#6-scaling-roadmap

RobLach•53m ago
MoS2 lattice construction?
matt123456789•29m ago
I suspect you are being downvoted because your answer is AI-generated, but I found it very clear and will upvote.
binyu•24m ago
What makes you think his reply was AI generated?

Edit: I can see a bunch of hints, most definitely. Still a good comment though.

binyu•29m ago
> they scale out in 2D, we scale up in 3D.

This actually helps a lot, thanks.

> Instead of spreading SRAM across a wafer, we stack DRAM on top of the logic

Is this done with current manufacturing technologies? Does it require a special process?

> no streaming, no off-chip memory at all. ~1 kW, not 23 kW

Is this for an individual compute unit? Compared to Cerebras, what's the ratio of power used vs compute output?

JumpCrisscross•55m ago
Can you explain why?
minkowsky•47m ago
I have a detailed comparison with Cerebras in economic analysis: https://www.phantafield.com/whitepaper#7-economic-analysis
wmf•2m ago
I'm questioning technical risks such as BEOL transistors and 2T DRAM cell structure, not the economics. Cerebras has already retired their technical risk.