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Dependency Resolution Methods

https://nesbitt.io/2026/02/06/dependency-resolution-methods.html
1•zdw•21s 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•42s ago•0 comments

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

https://www.iplotcsv.com/demo
1•maxmoq•1m 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•2m ago•0 comments

List of unproven and disproven cancer treatments

https://en.wikipedia.org/wiki/List_of_unproven_and_disproven_cancer_treatments
1•brightbeige•2m ago•0 comments

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

https://github.com/debugmeplease/debug-ME
1•debugmeplease•2m ago•1 comments

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

1•gogo61•5m ago•1 comments

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

https://paperinvest.io/arena
1•andrenorman•7m ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•11m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•11m ago•0 comments

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

https://github.com/ricardomoratomateos/distill
1•ricardomorato•11m 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•11m 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•13m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•13m ago•0 comments

Software Factories and the Agentic Moment

https://factory.strongdm.ai/
1•mellosouls•14m ago•1 comments

The Neuroscience Behind Nutrition for Developers and Founders

https://comuniq.xyz/post?t=797
1•01-_-•14m ago•0 comments

Bang bang he murdered math {the musical } (2024)

https://taylor.town/bang-bang
1•surprisetalk•14m ago•0 comments

A Night Without the Nerds – Claude Opus 4.6, Field-Tested

https://konfuzio.com/en/a-night-without-the-nerds-claude-opus-4-6-in-the-field-test/
1•konfuzio•16m ago•0 comments

Could ionospheric disturbances influence earthquakes?

https://www.kyoto-u.ac.jp/en/research-news/2026-02-06-0
2•geox•18m ago•1 comments

SpaceX's next astronaut launch for NASA is officially on for Feb. 11 as FAA clea

https://www.space.com/space-exploration/launches-spacecraft/spacexs-next-astronaut-launch-for-nas...
1•bookmtn•19m ago•0 comments

Show HN: One-click AI employee with its own cloud desktop

https://cloudbot-ai.com
2•fainir•21m ago•0 comments

Show HN: Poddley – Search podcasts by who's speaking

https://poddley.com
1•onesandofgrain•22m ago•0 comments

Same Surface, Different Weight

https://www.robpanico.com/articles/display/?entry_short=same-surface-different-weight
1•retrocog•24m ago•0 comments

The Rise of Spec Driven Development

https://www.dbreunig.com/2026/02/06/the-rise-of-spec-driven-development.html
2•Brajeshwar•29m ago•0 comments

The first good Raspberry Pi Laptop

https://www.jeffgeerling.com/blog/2026/the-first-good-raspberry-pi-laptop/
3•Brajeshwar•29m ago•0 comments

Seas to Rise Around the World – But Not in Greenland

https://e360.yale.edu/digest/greenland-sea-levels-fall
2•Brajeshwar•29m ago•0 comments

Will Future Generations Think We're Gross?

https://chillphysicsenjoyer.substack.com/p/will-future-generations-think-were
1•crescit_eundo•32m ago•1 comments

State Department will delete Xitter posts from before Trump returned to office

https://www.npr.org/2026/02/07/nx-s1-5704785/state-department-trump-posts-x
2•righthand•35m ago•1 comments

Show HN: Verifiable server roundtrip demo for a decision interruption system

https://github.com/veeduzyl-hue/decision-assistant-roundtrip-demo
1•veeduzyl•36m ago•0 comments

Impl Rust – Avro IDL Tool in Rust via Antlr

https://www.youtube.com/watch?v=vmKvw73V394
1•todsacerdoti•36m ago•0 comments
Open in hackernews

Replacing Markowitz: A Quantum Approach to Portfolio Optimization

https://soma.biz/
4•Hellene•2mo ago

Comments

7777777phil•2mo ago
Cool Project. Been working on something similar in my undergrad days[1]. Is there a paper / repository showing the math and tech behind it?

[1]https://philippdubach.com/2024/03/15/my-first-optimal-portfo...

Hellene•2mo ago
Oh thank you so so much for sharing your research on related topic. I will read it and let you know more :). Thank for drop me feedbacks :). Please have a very great day.
Hellene•2mo ago
Hi, Your blog is very interesting. However, the approach you described is a classical one: most current portfolio optimization software uses the Markowitz Mean-Variance framework to determine the optimal allocation of capital among preselected assets. This method works well for large portfolios and for investors with a strong finance background, as they typically know in advance which assets to include based on their analysis.

However, this approach has limitations. It requires asset managers to spend significant time and effort selecting the assets beforehand, and it cannot explore all possible combinations of assets, which means the resulting portfolio might not be globally optimal. In classical computing, an exhaustive search of all possible combinations is called brute force, but this quickly becomes impractical: for example, considering just 10 assets with simple inclusion/exclusion yields 2¹⁰ = 1,024 combinations, and the number grows dramatically if allocation weights are included.

This is why quantum portfolio optimization (the approach used by our platform) is innovative: it leverages quantum computing to explore many combinations simultaneously, enabling the optimization of large portfolios in real time, even for users without deep financial expertise.

Hellene•2mo ago
Hi,

Your blog is very interesting. However, the approach you described is a classical one: most current portfolio optimization software uses the Markowitz Mean-Variance framework to determine the optimal allocation of capital among preselected assets. This method works well for large portfolios and for investors with a strong finance background, as they typically know in advance which assets to include based on their analysis.

However, this approach has limitations. It requires asset managers to spend significant time and effort selecting the assets beforehand, and it cannot explore all possible combinations of assets, which means the resulting portfolio might not be globally optimal. In classical computing, an exhaustive search of all possible combinations is called brute force, but this quickly becomes impractical: for example, considering just 10 assets with simple inclusion/exclusion yields 2¹⁰ = 1,024 combinations, and the number grows dramatically if allocation weights are included.

This is why quantum portfolio optimization (the approach used by our platform) is innovative: it leverages quantum computing to explore many combinations simultaneously, enabling the optimization of large portfolios in real time, even for users without deep financial expertise.