JPMorgan CEO Jamie Dimon says other bank exec could have booted Jeffrey Epstein as customer
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Points: 140
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Article URL: https://aswinmohan.me/better-fonts-on-linux
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Article URL: https://aisnakeoil.substack.com/p/is-avoiding-extinction-from-ai-really
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Points: 97
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Points: 28
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My designer is somewhat special, if I do say so myself, as it allows you to put arbitrary designs in the middle area of the QR while still being totally scannable.
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Points: 10
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Article URL: https://www.interactions.org///press-release/lhc-experiments-see-first-evidence-rare-higgs-boson-decay
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Points: 20
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Article URL: https://phys.org/news/2023-05-fossil-tail-ancient-beast.html
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Points: 5
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Article URL: https://www.scientificamerican.com/article/gdp-is-the-wrong-tool-for-measuring-what-matters/
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Article URL: https://github.com/s0md3v/roop
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Points: 37
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Article URL: https://jacobin.com/2023/05/private-equity-hospice-care-profit-regulation
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Points: 23
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Article URL: https://www.salon.com/2023/03/16/health-officials-delayed-report-linking-fluoride-to-brain-harm_partner/
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Points: 41
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Points: 26
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Article URL: https://www.nytimes.com/2023/05/28/science/ian-hacking-dead.html
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Article URL: https://httpwg.org/http-extensions/draft-ietf-httpbis-safe-method-w-body.html
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Article URL: https://blog.replit.com/super-colliding-nix-stores
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Article URL: https://hackaday.io/project/191142-analog-lorenz-attractor-computer
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Points: 33
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Article URL: https://www.axios.com/2023/05/18/once-a-fringe-theory-greedflation-gets-its-due
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Points: 19
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My cofounder and I used to work at Robinhood where we shipped the company’s first OAuth integrations, so we know a lot about how data moves between companies.
For example, we know that the pain of building new API integrations scales with the fragmentation in the industry. In the current meta, we see this pain with a lot of AI startups who invariably need to connect to their customers data, but have to support 50+ integrations before they even scale to 50+ customers.
This is the process for an AI startup to add a new integration for a customer:
- Pore over the API docs for each source application and write a connector for each - Play email tag to find the right stakeholders and get them to share sensitive API keys, or give them an OAuth app. It can take 6+ weeks for some platforms to review new OAuth apps - Normalize data that arrives in a different formats from each source (HTML, XML, text dumps, 3 different flavors of markdown, JSON, etc) - Figure out what data should be vectorized, what should be stored as SQL, and what should be discarded - Detect when data has been updated and synchronize it - Monitor when pipelines break so data doesn’t go stale
This is a LOT of work for something that doesn’t move the needle on product quality, so it’s no wonder that most startups are still relying on file uploads to onboard their early customers. The problem is file uploads are slow and insecure and don't scale.
That’s why we built Psychic.dev to be the fastest and most secure way for startups to connect to their customer’s data. You integrate once with our universal APIs and get N integrations with CRMs, knowledge bases, ticketing systems and more with no incremental engineering effort.
We abstract away the quirks of each data source into Document and Conversation data models, and try to find a good balance to allow deep integrations while preserving general purpose utility. Since it’s open source, we encourage founders to fork and extend our data models to fit their needs as they evolve, even if it means migrating off our paid version.
To see an example in action, check out our demo repo here: https://github.com/psychic-api/psychic-langchain-tutorial/
We are also open source and open to contributions, learn more at docs.psychic.dev or by emailing us at founders@psychic.dev!
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Points: 10
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Article URL: https://www.nature.com/articles/s41593-023-01333-4
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Points: 4
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Here is a screenshot of my Bitwarden: https://ift.tt/qcdoY4N
They include some really important things such as:
Health insurance G-Suite for work Bill.com (which I use to get paid) IRS.gov (which I use to get un-paid) UK Companies House Register Interactive Brokers My bank
Obviously, anything with OAuth is "bundled" into my Google account. So if anything this is a huge underestimate.
I'm asking because of how insane auth has become. I know companies like OnePassword and Bitwarden are working on this and overall they do a great job. But I still have a near-stroke every time I have to do the "forgot my password" loop, or use Duo Mobile/other 2FA.
The only really good auth feature I've ever encountered has been Apple's "fill from Messages" feature as well as their Touch.
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Points: 43
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Article URL: https://github.com/stepchowfun/typical
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Points: 1
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Article URL: https://status.python.org
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Points: 29
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Points: 28
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Points: 6
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Points: 9
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Article URL: https://www.tomshardware.com/news/intel-ponders-transition-to-64-bit-only-x86s-architecture
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Points: 43
# Comments: 11
Article URL: https://www.thedefensepost.com/2023/05/18/us-drone-swarm-thor/
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Points: 34
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Article URL: https://reality.mentat.org/essays/reality/introduction
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Points: 12
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Article URL: https://torrentfreak.com/anti-piracy-program-accused-of-violating-citizens-fundamental-rights-230519/
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Points: 29
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Article URL: https://github.com/ziglang/zig/blob/7cf2cbb33ef34c1d211135f56d30fe23b6cacd42/test/standalone/http.zig
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Points: 17
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Article URL: https://empathynovel.substack.com/p/dear-substack-quit-sending-me-your
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Points: 22
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Article URL: https://blog.mastermind.dev/indexes-in-postgresql
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Points: 14
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Article URL: https://krebsonsecurity.com/2023/05/re-victimization-from-police-auctioned-cell-phones/
Comments URL: https://news.ycombinator.com/item?id=35961032
Points: 33
# Comments: 1
Hey HN, my name is Vikas, and my cofounders Rish, Gabe and I are building Openlayer: http://openlayer.com/
Openlayer is an ML testing, evaluation, and observability platform designed to help teams pinpoint and resolve issues in their models.
We were ML engineers experiencing the struggle that goes into properly evaluating models, making them robust to the myriad of unexpected edge cases they encounter in production, and understanding the reasons behind their mistakes. It was like playing an endless game of whack-a-mole with Jupyter notebooks and CSV files — fix one issue and another pops up. This shouldn’t be the case. Error analysis is vital to establishing guardrails for AI and ensuring fairness across model predictions.
Traditional software testing platforms are designed for deterministic systems, where a given input produces an expected output. Since ML models are probabilistic, testing them reliably has been a challenge. What sets Openlayer apart from other companies in the space is our end-to-end approach to tackling both pre- and post-deployment stages of the ML pipeline. This "shift-left" approach emphasizes the importance of thorough validation before you ship, rather than relying solely on monitoring after you deploy. Having a strong evaluation process pre-ship means fewer bugs for your users, shorter and more efficient dev-cycles, and lower chances of getting into a PR disaster or having to recall a model.
Openlayer provides ML teams and individuals with a suite of powerful tools to understand models and data beyond your typical metrics. The platform offers insights about the quality of your training and validation sets, the performance of your model across subpopulations of your data, and much more. Each of these insights can be turned into a “goal.” As you commit new versions of your models and data, you can see how your model progresses towards these goals, as you guard against regressions you may have otherwise not picked up on and continually raise the bar.
Here's a quick rundown of the Openlayer workflow:
1. Add a hook in your training / data ingestion pipeline to upload your data and model predictions to Openlayer via our API
2. Explore insights about your models and data and create goals around them [1]
3. Diagnose issues with the help of our platform, using powerful tools like explainability (e.g. SHAP values) to get actionable recommendations on how to improve
4. Track the progress over time towards your goals with our UI and API and create new ones to keep improving
We've got a free sandbox for you to try out the platform today! You can sign up here: https://app.openlayer.com/. We are also soon adding support for even more ML tasks, so please reach out if your use case is not supported and we can add you to a waitlist.
Give Openlayer a spin and join us in revolutionizing ML development for greater efficiency and success. Let us know what you think, or if you have any questions about Openlayer or model evaluation in general.
[1] A quick run-down of the categories of goals you can track:
- Integrity goals measure the quality of your validation and training sets
- Consistency goals guard against drift between your datasets
- Performance goals evaluate your model's performance across subpopulations of the data
- Robustness goals stress-test your model using synthetic data to uncover edge cases
- Fairness goals help you understand biases in your model on sensitive populations
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Points: 28
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Article URL: https://en.wikipedia.org/wiki/Pfeilstorch
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Points: 25
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Article URL: https://colab.research.google.com/github/norvig/pytudes/blob/main/ipynb/Goldberg.ipynb
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Points: 4
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Article URL: http://www.catb.org/~esr/writings/cathedral-bazaar/cathedral-bazaar/
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Points: 18
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Points: 33
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Article URL: https://www.indiehackers.com/post/how-to-hack-hacker-news-and-consistently-hit-the-front-page-56b4a04e12
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Points: 54
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Article URL: https://www.nature.com/articles/s41587-022-01618-2
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Points: 18
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Points: 10
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Points: 16
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Points: 15
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Article URL: https://techcrunch.com/2023/05/10/google-makes-its-text-to-music-ai-public/
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Points: 16
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Article URL: https://www.abc.net.au/news/2023-03-09/monash-university-air-electricity-enzyme-soil/102071786
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Points: 18
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Points: 8
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Points: 16
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Article URL: https://techcrunch.com/2023/05/10/google-launches-palm-2-its-next-gen-large-language-model/
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Points: 39
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Article URL: https://educatedguesswork.org/posts/unwanted-tracking/
Comments URL: https://news.ycombinator.com/item?id=35877825
Points: 4
# Comments: 1
This is a project I've been working on for a little while and I'm interested in your feedback and point of view.
The Domain Verification protocol stores a DNS TXT record at a DNS name derived from a hashed "verifiable identifier" (email, telephone, DID), enabling anyone that can prove control over the verifiable identifier to prove authority for the domain name, whilst preserving the privacy of the authorised party.
Once setup, the record enables automatic domain verification for any service provider.
This record could be automatically setup by domain registrars upon domain registration (with registrant opt-in) creating a fast lane for verification with service providers many new small businesses use (eg Google Ads, Facebook, Office365, Dropbox, etc).
=====
Many of us would have verified a domain name by pasting a string into a DNS TXT record. These methods are currently being discussed and standardised at the IETF [2].
Let's Encrypt's DNS-01 method [3] is probably considered the state of the art. The differences between DNS-01 and Domain Verification protocol are:
- DNS-01 requires a new TXT record for each service provider. With Domain Verification Protocol, multiple service providers can use the same record.
- Instructions to setup a DNS-01 TXT record are instigated by the service provider, whereas a Domain Verification Protocol record can be setup independently by a user or a domain registrar. They could even pre-populated by a registrar upon domain registration (with registrant opt-in)
- There’s no concept of permissions in DNS-01, the act of creating the record gives the user full access for the domain with the service provider. With Domain Verification protocol multiple records can be setup, limited permissions could be setup for different third parties. For example give a marketing agency authentication to claim the domain on social media but nowhere else.
I'm still working on licensing but creating these records will always be free. I hope to find service providers that see significant upside in reducing friction for user onboarding that are willing to pay to license it.
Worked example: Let's say you want to authenticate the user with the email user@example.com with the domain dvexample.com, these are the steps:
a. HASH(user@example.com) -> 4i7ozur385y5nsqoo0mg0mxv6t9333s2rarxrtvlpag1gsk8pg
b. Store Domain Verification record at: 4i7ozur385y5nsqoo0mg0mxv6t9333s2rarxrtvlpag1gsk8pg._dv.dvexample.com
c. TXT record determines permissions and time limit:
@dv=1;d=Example user email;e=2025-01-01;s=[seo;email];h=4i7ozur385y5nsqoo0mg0mxv6t9333s2rarxrtvlpag1gsk8pg
Thanks for taking a look,
Elliott
1. https://news.ycombinator.com/item?id=35827952
2. https://datatracker.ietf.org/doc/draft-ietf-dnsop-domain-ver...
3. https://letsencrypt.org/docs/challenge-types/
=====
Quick sidebar:
This was originally submitted to HN under the title "Show HN: Make domain verification as easy as verifying an email or phone number" 3 days ago [1]. It was doing really well (#3 on front page) then totally disappeared from front page and went to bottom of page 1 of Show HN.
After an email exchange with dang (incredibly helpful as always), he explained that it got flagged with the "overheated discussion detector" and it turned out I caused this by diligently responding to every comment as fast as my fingers would type because I wanted to keep engagement going. Helpfully dang took the flag off it about 12 hours later after our email exchange, but understandably the momentum was lost.
So I feel like it kinda got killed, just as it was picking up pace and as the US west coast was waking up. So I am humbly reposting it with a modified description based on the comments of the last post.
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Points: 15
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Article URL: https://librivox.org/
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Points: 29
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What tools do you use to keep track of your daily tasks, projects, and other obligations?
What do you like about these tools and what would you like to change?
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Points: 18
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Points: 19
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Points: 37
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Article URL: https://securityonline.info/intel-oem-private-key-leak-a-blow-to-uefi-secure-boot-security/
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Points: 103
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Article URL: https://reaganray.com/2020/05/12/sci-fi-movie-lettering.html
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Points: 9
# Comments: 1
In the past few days, there have been uncertainties and concerns about the LUKS (“Linux Unified Key Setup”) disk encryption, which is widely used on Linux. We publish our assessment of this here.
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Points: 12
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Points: 18
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Points: 33
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Points: 49
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Article URL: https://www.science.org/content/article/brazilian-frog-might-be-first-pollinating-amphibian-known-science
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Points: 28
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Points: 40
# Comments: 5
Share your information if you are looking for work. Please use this format:
Location:
Remote:
Willing to relocate:
Technologies:
Résumé/CV:
Email:
Readers: please only email these addresses to discuss work opportunities.
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Points: 40
# Comments: 103