skysight-inc/HackerNews huggingface dataset:
Emacs-termux is awkward to get working initially, but it gives you more-or-less full emacs as an Android app, but sharing storage/namespace with termux so that they both have access to the same binaries and documents.

There isn't a good project page, it's based at this sourceforgw page and has a surprisingly comprehensive readme.

https://sourceforge.net/projects/android-ports-for-gnu-emacs...
If it's in the territory of ex employees being forced to sign something, I don't count that under NDA anymore - it's just sneaky BS. You can twist anything in some evil scheme - that doesn't mean the original thing itself is bad.

The context here is sharing general technical knowledge, not the openai internal backstabbing.
Well you can piss people off in some ways, yet in other ways give them value.
It's just ideological drivel. People never had any difficulty to cooperate on such level.
Demis understands the “customer” and can use everything he has learned in the last 20 years to build something incredible. If he can build a great/successful game with low resources, he will smash a consumer product with unlimited resources and excellent people.
> Every place I've ever worked which tried this has managed to get a production database deleted by somebody running tests.

That's just a different way of saying "Every place I've ever worked at use production for testing" :-/

TBH, any place using the same credentials for test and for production have bigger problems than would ever be fixed by mocking.
In 2016, Tesla released the Model 3. When Chinese consumers wanted the most advanced electric vehicles, the Chinese government communicated with Tesla in 2017 about building a factory in Shanghai to produce China-made Teslas. Currently, Tesla is the highest-selling pure electric vehicle brand in China ( Model Y sales in China in December last year were 60,055 volumes
) The intense competition in the electric vehicle market has fostered the development of high-quality Chinese EV brands such as NIO, Li Auto, XPeng, BYD, Zeekr, Xiaomi, Aion... ...
In contrast, in the free and democratic America market, the response to competition in the drone market has been to ban DJI, and the response to competition in the short video market has been to ban tiktok.
Let’s see in ten years which market environment will foster advanced productivity.
I'm not really sure where i stand on this - as someone in the throws of self teaching programming (C) - and consider myself pretty smart. I've attempted learning on my own several times. Many times since 2016 and have given up on many occasions. CS50x is one of the first pieces of material which has close to what i consider sane pedagogy.

I go back and forth between thinking Python is better for learning because "hey, less typing, less curly braces". Then thinking - great i dont know wtf is happening here - just magic i guess?? (refer XCXD comic).

I have seen this many times in relation to education and quite simply, the way we teach, often "for speed", and "at university" - do not equate to learning anything. Learning how things works for real - takes time, and is often outside the scope of a "semester"...and quite honestly beyond our current paradigms of cordoned off disciplines.

Programming/algorithmic thinking is more or less hardware accelerated mathematics. When i opened up Hammack's - How to Prove it - and read about sets, saw the notation - AHA moment. Similar things happened when looking at Charles Petzold's Code and seeing details of carry bits in counter chips, and comparing those to literal carry pins in gear based mechanical calculators (in Norman Bigg's "Quite Right").

None of this comes naturally (to me) - and i think many of the learning resources are there - but are not there at the time you need them. Common comments "just do a project"..."get out of tutorial hell"...very well meaning...but even a 1000 LOC text editor is an absolute head fuck for someone who just learnt to print a triangle of hashes.

I've reached out to the creator of the Turing Complete PC game on Steam. I'm certain once virtualising a computer which runs C in that game - will we reach the epitome of programming pedagogy :-)
Processing but for webdevs?
There are many natural products which have a similar magic. Cork, sheep wool, bees wax, &c.

And yes most alternative leathers are plastic with 10% of something in top so you can call it "apple" leather, "pine apple" leather, ... Or straight up petrol derivates
TLDR: A GCR exposure with a dose-equivalent to a Mars roundtrip induces renal damage and dysfunction

Acute exposure to simulated GCR causes both acute and chronic tubular epithelial and vascular damage that appears both progressive and irreversible.
The nice thing is that if this dot-approach (or some other syntax with a similar effect) were implemented in Futhark, then because Futhark is statically-typed, all mismatches would be compile-time errors. Those are very hard to overlook :)
Those aren't sources. They aren't where the model got the information (that info isn't stored in an LLM).

Rather, such AI systems have two parts: an LLM that writes whatever, and a separate system that searches for links related to what the LLM wrote.
We are, that is why at the end of the day language like Go evolve into a kludge of poorly integrated designs, and the anti-complexity folks discover that those complex features exist for a reason, and then have to try to implement them into their earlier design decisions.

We have been through this reboots multiple times, Pascal vs Algol 68, C vs PL/I, Java vs C++, ....

Now compare where those "simpler" languages are 20 to 50 years later, compared with their version 1.0, and the amount of "could it been better" features if they were there in version 1.0.

Go folks, thought they are special and this wouldn't happen to them.
Sure, but it can semantically query a vector DB on the side and use the results to generate a "grounded" response.
New study finds potential alien mega-structures known as 'Dyson spheres'
There seems to be this great dellusion being spread that it would not be such a big deal to not make people dissent.

You can notice it in how people reason about 'war time manufacturing' and the like in the event of a Great war. Like there would be any factories running at all. Or logistics to support brigade manouvers. Or state sized organizations.
Cloud-hosted loan management solutions have emerged as a game-changer for financial institutions. These solutions leverage the power of the cloud to streamline lending operations, enhance efficiency, and improve customer experience. With the increasing demand for digital transformation in the banking sector, adopting a cloud-based approach to core lending software has become essential. This blog post will explore the benefits of cloud loan management solutions, discuss key considerations for implementation, and highlight how this technology can transform lending operations.

Benefits of Cloud Loan Management Solutions
Enhanced Efficiency and Scalability
One of the primary advantages of cloud loan management solutions is the significant boost in efficiency and scalability they offer. Traditional lending operations often involve cumbersome manual processes and disparate systems, leading to delays and errors. Cloud-based solutions integrate seamlessly with core banking systems, automating workflows and reducing the need for manual intervention.

With commercial loan software hosted on the cloud, financial institutions can easily scale their operations to meet changing demands. Whether it's expanding the loan portfolio, managing peak application periods, or entering new markets, the cloud provides the flexibility needed to adapt quickly. This scalability is particularly beneficial for institutions looking to grow their business without the constraints of legacy systems.

Improved Security and Compliance
Security and compliance are paramount concerns for any financial institution. Cloud loan management solutions offer robust security measures to protect sensitive customer data and ensure compliance with regulatory requirements. Leading cloud providers invest heavily in state-of-the-art security technologies, including encryption, multi-factor authentication, and advanced threat detection.

Moreover, cloud solutions often come with built-in compliance features that help financial institutions adhere to industry standards and regulations. This is particularly important in the ever-changing regulatory landscape of the financial sector. By leveraging cloud-based commercial loan software, institutions can reduce the risk of data breaches and ensure that their lending operations are always compliant.

Enhanced Customer Experience
In today's competitive market, providing an exceptional customer experience is crucial for retaining clients and attracting new ones. Cloud loan management solutions enable financial institutions to offer a seamless and user-friendly experience to borrowers. With real-time access to information and streamlined processes, customers can enjoy faster loan approvals and more transparent communication.

Cloud-based systems also support omnichannel capabilities, allowing borrowers to interact with the institution through their preferred channels, whether it's online, mobile, or in-branch. This flexibility enhances customer satisfaction and loyalty, positioning the institution as a forward-thinking and customer-centric organization.
reminds me of the coffee shop incident in seattle last week with the hammer
Last month they unblocked me even though the website is blank.
I agree about directives embedded in comments. Especially things like // go:embed

But goroutines? They are a foundational language feature with clear syntactic demarcation and documented behaviour.

I think that in computer science "Magic" doesn't mean that the implementation is hard to understand. Magic means that the behavior is surprising, that there is misdirection involved etc
What kind of work? I've only given it a short try before moving to Ollama that doesn't have it, but it seemed to have worked there. (With ollama I need to use a retry system.)

edit: I researched a bit and apparently it can reduce performance, plus the streaming mode fails to report incorrect grammars. Overall these don't seem like deal-breakers.
Extract sensitive data from Android 12/13 apps via "run-as" forgery
Some context:

CVE-2024-0044 - https://nvd.nist.gov/vuln/detail/CVE-2024-0044

> In createSessionInternal of PackageInstallerService.java, there is a possible run-as any app due to improper input validation. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

Bypassing the "run-as" debuggability check on Android via newline injection - https://rtx.meta.security/exploitation/2024/03/04/Android-ru...

Exfiltrate sensitive user data from apps on Android 12 and 13 using CVE-2024-0044 vulnerability - https://www.mobile-hacker.com/2024/06/17/exfiltrate-sensitiv...
that's a great question, there's three main benefits:

1. seeing the full prompt, even though that python code feels leaner, somehow you need to convert it to a prompt. a library will do that in some way, BAML has a VSCode playground to see the entire prompt + tokenization. If we had to do this off of python/ts, we would run into the halting problem and making the playground would be much much harder.

2. there's a lot of codegen we do for users, to make life easier, e.g. w/o BAML, to now do streaming for the resume, you would have to do something like this:

class PartialResume:
name: Optional[str]
education: List[PartialEducation]
skills: List[str]

and then at some point you need to reparse PartialResume -> Resume, we can codegen all of that for you, and give you autocomplete, type-safety for free.

3. We added a lot of static analysis / jump to definition etc to JINJA (which we use for strings), and that is much easier to navigate than f-strings.

4. Since its code-gen we can support all languages way easier, so prompting techniques in python work the same exact way for the same code in typescript.
The study of consciousness (or sentience or whatever the appropriate term is) is definitely a valid field of research and one of science and philosophies all-time greatest mysteries. What exactly is the underlying mechanism and theory of consciousness? For example, A sound scientific theory of consciousness should be able to definitively answer the questions (and defend that answer):

- Is an ant sentient? Why ? Why not? What is it aware of?
- What about an amoeba? a bacteria? a virus? a cell? At what level does it stop?
- What about the plant kingdom?
- A rock? An atom? Why? Why not?
- An LLM? A program? A computer?..
- Will an AGI be sentient ?

The premise of the article itself is strange - maybe it was intended to stir up debate and controversy. Its one thing to say that study of consciousness lacks sound foundations. But implying the very notion that "animals are conscious" is somehow controversial? If animals aren't conscious whats the point of animal cruelty or animal welfare laws? I can take a power drill to my roomba but can i do the same to a cat or a dog? Most people would automatically say no. Its something most people intuitively understand (but maybe its learned behaviour - kids can be cruel until they learn empathy).

edit : Also the illy-dallying around the question of crustaceans seems shifty. Maybe the authors don't want to confront the moral question of boiling lobsters alive?
This assumes a fair market.

Most (all?) arguments that depend on competition depend on a fair market.

However, no industry or government lives in a vacuum.

Firm X develops enough market dominance to constantly collect vast sums of money to build their war chest.

This war chest is used to buy out competitors, and kill off competing ideas.

Firm X creates clones of lower priced alternatives, then outcompetes the smaller firm.

Firm X uses war chest to fob off or weaken regulators (if any exist), extending the time they can extract rents.

——

Little guys have to survive by getting enough money fast enough to beat the Big guy. Why bother? Get moderately sized, get bought out, and live with your wealth.

PS: I have butchered economics somewhere, forgive me.
And the tick based SQL + Java engine was built in 2004 when it migrated from RS classic to RS2.
Two big advantages.

First, if you want a declarative config with limited, domain-specific options, rolling your own DSL instead of using something as complex as Python is much, much easier to implement. You're not actually going to be running the code either way, at least not in the normal way, and the Python syntax tree is pretty complicated.

Second, having code that looks like Python can lead your users to believe that it is in, in fact, Python. When you're doing things like using your DSL as configuration that happens at setup time, but then actually "running" the resulting config later on, that can lead to people getting themselves into trouble - for instance, they might try to use `time.now()` and end up embedding the time of the config parser as a constant in their workflow definition.

If you want to use Python as your language, you probably want to define your "DSL" as a Python library, so that you can use a normal interpreter to work with it. Maybe you have library functions that return config objects, and a user's "configuration" is an arbitrary Python file with a standard function name as an entry point. But then when you want to introspect over types, you probably need to start playing games with decorators, which is tricky again, and you have to be very careful to have that evaluation step return meaningful errors.

Starlark (https://github.com/bazelbuild/starlark) is an example of using Python-ish as a "configuration" language. That took an absolutely massive amount of engineering to get to be well-defined, and was only arguably worth it because they wanted a language that's a loop construct away from being Turing-complete. If they had wanted a basic declarative relationship language, they probably would have used textprotos or GCL.
The Most Ramified Chess Position of 2023
The genius of photolithography is many things, I wouldn't say the wafer process is any more special than the statistical models that can predict where a nozzle needs to point to lay substract with more precision than the nozzle itself can provide or a number of other important inventions there.
Right, very like me. Language is the front end; I use it to express thoughts when needed (to record, communicate and check reasoning) The back end is working in some kind of abstract space.

I suspect people who say they think in language are not really thinking "in" language. I think we all have this abstract conceptual space in us. I'm not even sure what it means to think in language; where do the ideas and concepts come from that are being expressed? I guess some people have to internally "hear" a thought expressed before it is real to them.
Influence != Determine
That's totally true and something I don't know the answer to. But it's interesting to ponder if the experience of consciousness is the same for each individual. We believe that consciousness is possibly an emergent phenomena of cognitive processing, but since there is a wide amount of heterogeneity in the makeup of the human mind, it isn't extraordinary to claim that this 'presence in the current moment' may have different flavors for different individuals.

The claim that certain individuals lack an inner monologue is a testament to this—I can't imagine what that would be like but that is certainly nothing like my conscious experience is. To me, the lack of an inner monologue sounds very much like the 'dark universe' in which the brain is doing all of the processing and there is no conscious observer to witness the unfolding. I'm sure people without a inner monologue are still conscious.. but—it's interesting to think about how different their experience may be like.
Your mentor finds you.

Mentoring someone is giving. And not having anything in return, at least for years. Or ever.

So, for someone to mentor you, you have to be interesting to them.

Ask yourself this question, as you are at least somewhere in life- "If I were to mentor someone, what would that person have to do/have?"

Now reverse this, and identify qualities in you that you can leverage to find a mentor.

Mentoring is a long term thing. So, instead of finding mentor deliberately, get to know a lot of people. Among them, ask some people advice about some specific things. That one advice seeking might turn into two, or they might start giving you more advices, more broader ones, too.

Just expose yourself to a lot of interesting people and stay in touch with people you are genuinely interested to know, or can admire.

Be an interesting kind of person. I found my first (tech) mentor because he could talk international news with me (I did a lot of debate when I was young), my second one appeared in my life when I was organizing cultural programmes, and charity for disadvantaged kids. I met my last one, who is also a friend in an online study group.

Also look for similar backgrounds. I was interested in mentoring someone as he really liked extra curricular learning, and made great web apps. He also, like me, migrated to tech from something else.
That level of contempt for the people around you is exactly why tech companies can't even create something as boring as a taxi company or corporate shuttle without raising the ire of everyone else.
btw that's not how tools work at all. Tools are function/API based. (Unless you expose a function run_sql(query), but that's on you.)
I think OpenAI was chilled out, and mostly lucky. Chilled in the sense that Google seems to be too full of itself, and their practice of publishing groundbreaking research without actually publishing anything other people can use is, frankly, annoying. OpenAI managed to leapfrog them by slapping a chat interface on a tuned GPT-3 and putting it on the Internet.

The chat service bit is them being chill, but the real spark was the model. I say they were lucky, because AFAIK back then no one expected LLMs to show so many and so advanced general capabilities. This took everyone by surprise, and since people could already play with it, ChatGPT took off on its own - it had so much real, transformative value, that it spread out with zero marketing. That's a rare, bona fide case of "word of mouth", it was just that useful. But that wasn't a strategy, that was luck.

To their credit though, OpenAI turned this early win into an opportunity and is excellent at exploiting it. Being small helps.
I'm not sure where you are reading but both layman and scientists commonly use the word "human" to refer to the genus "homo". To look at just one example, Ian Tattersall called one of his books "Extinct Humans" and it is a look at the history of the genus homo:

https://www.amazon.com/Extinct-Humans-Ian-Tattersall/dp/0813...
> Adobe doesn’t really have many offerings for musicians.

I dont know about that, Ive made many songs in Adobe Flash in my time! /s
So, it's still bits all the way down? Whether we're talking about app, IP, or LL it's always bits/s, each level bringing a cost due to encapsulation. And then at PHY there's baud.

Is non-ISO unit "T" / "transfer" a marketing term or really specialised jargon? "transfer" just doesn't click in my mind, at best "a transfer" (countable) is about moving a sizeable aggregate chunk that has some semantic meaning, not a single fundamental quantum of information.

Unrelated: "gigatesla per second" is such a mind-boggling unit.
Threads launches its API for developers
Also, it doesn’t really have a solution. There are safe ways to concurrently access the same memory region, that rust disallows without unsafe, and if you are writing a high-performance language runtime you might well need these features.
It’s even worse on here since the HN audience seems to worship Altman, although table seem to have turned and he is a bad guy now. Can’t make this stuff up
ADP Research: The rise–and fall–of the software developer
Is it magic?

The reason they changed the behaviour is because the previous behaviour was surprising and thus "magical". The new behaviour is more consistent with what you think about what is a scope of a variable.

The fact that a compiler has to add some code to instantiate a variable is not magical. Otherwise all what compilers do would be magical
Could these processors help Intel move further into AI inference?
Why not apply it at an earlier layer then?
There seems to be a very common misconception about branch prediction, that its only job is to predict the direction of the branch.

In reality, the problem is so much deeper. The instruction fetch stage simply can't see the branch at all. Not just conditional branches, but unconditional jumps, calls and even returns too.

Even a simple 5 stage "classic RISC" pipeline takes a full two cycles to load the instruction from memory and decode before it can see it, and your instruction fetch stage has already fetched two incorrect instructions (though many RISC implementations cheat with an instruction cache fetch that takes half a cycle, and then adding a delay slot).

In one of these massive out-of-order CPUs, the icache fetch might take multiple cycles, (then length decoding on x86), so it might take 4 or 5 cycles before the instruction could possibly be decoded. And if you are decoding 4 instructions per cycle, that's 20 incorrect instructions fetched from icache.

To actually continue fetching without any gaps, the branch predictors needs to predict:

1. The location of the branch

2. The type of branch, and (for conditional branches) if it's taken or not.

3. The destination of the branch
You might be thinking of the Sex Pistols gig whose audience of 30-40 included Morrissey, Mark E Smith, the Buzzcocks and Lower Broughton: https://www.bbc.co.uk/manchester/content/articles/2006/05/11...

The docudrama 24 hour party people is good to watch about this era.
You can wrap a std::array into a std:unique_ptr, hardly much to write besides a couple of type alias.