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How does it compare to AutoMQ? (https://github.com/AutoMQ/automq)


AutoMQ look so so promising. Very happy to see the shift to Apache 2.0 license a couple month ago!! I do think it sounds like the most obvious comparison to Ursa: object-storage based, focus on removing inter-zone traffic. They also have a neat new Table Topics, that's super helpful. https://www.automq.com/docs/automq/eliminate-inter-zone-traf...

There's an OK high level cruise, WarpStream is dead, long live AutoMQ riffing off WarpStream doing similar against Kafka. While I loosely got the idea, I had to dig a lot deeper in docs for things to start to really click. https://github.com/AutoMQ/automq/wiki/WarpStream-is-dead,-lo...

There may be reasons it's a bad fit, but I'm expecting object-storage database SlateDB someday makes a very fine streaming system too!! https://github.com/slatedb/slatedb


I wanted to find the actual change performed by these agents so I watched the embedded video. I can not believe what I saw.

The video shows a private fork of a pubic repository. The bug is real, but it was resolved in February 2023 and doesn’t seem like the solution was automated [1]

The bug has a stack trace attached with a big arrow pointing to line 223 of a backend_compat.py file. A quick grasp on this stack trace and you already know what happened and why, and how to fix this, but…

not for the agent. It seems to analyze the repository in multiple steps and tries to locate the class. Why did they even release this video?

[1] https://github.com/Qiskit/qiskit/issues/9562


Mgmt at every company is asked - what are you doing to be agentic ?

so, they organize hackathons where devs build a hypothetical agentic framework nobody will dare use. So, mgmt can claim, look here what i have done to be agentic.

you should ask: would you dogfood your agent, and the answer is no way. these are meant purely for marketing purposes, as they dont meet an end user need.


whats hilarious in this farce is how these are being rebranded from "co-pilots" to "agents"

just goes to show, it is all a big song-and-dance. much ado about nothing.


The term "co-pilot" implies a company has to hire a software engineer to guide the AI.

The term "agent" implies you can give the AI full access to your repos and fire the software engineers you're grudgingly paying six figures to.

The second is much more valuable to executives not wanting to pay the software people that demand higher salaries than virtually everyone else in the organization.


They're was no rebrand. They're different concepts. Copilot and similar solutions are giving hints as you do the development. Agents are systems that receive a goal and will iterate actions and queries for more information until they achieve the goal.


you are quoting the party-line.

i am saying, the thing is snake-oil - a solution looking for a problem.


I'm explaining what words mean. Agentic approach has been a thing for years https://en.wikipedia.org/wiki/Intelligent_agent You can just say you don't like AI in programming, without saying incorrect things on top of that.


Right. Woe is the startup that doesn't have an AI story right now.


The companies that have a data moat and no AI are in a much better position than those who’ve got it the other way around.


Depends on what you are optimizing for.

Long term value, I agree.

Fundraising, hard disagree.


Classic machine learning researcher trick: just select your test example from the training set! It certainly saves a lot of effort.


That’s true, but this repo has thousands of bugs. They could at least find one that was in the training set, but also did not contain the location in the bug description.

This way it would at least look like it may work


Decision makers and those writing the check aren’t sophisticated enough to know the difference, in my experience with orgs that buy from IBM.


every hype cycle runs through a predictable course.

we are at a phase where the early adopters have seen the writing on the wall.. ie that llms are useful for a limited set of usecases. but there are lots of late adopters who are still awestruck and not disillusioned yet.


Indeed. It's also amusing how it produces a multi-page essay on the bug instead of submitting a pull request with an actionable fix.


The demo is not supposed to wow the technical people. The business people whose budgets will pay for this are less likely to notice.


I think the process could be better, but if you want good quality you really shouldn't expect it to just jump at the "obvious" thing. Just like you wouldn't want the developer to just make the error to away in the quickest way. Getting more context is always going to be a good idea, even if it wastes some time in the "trivial" cases.


it takes more time to watch the video than fix the bug


you can't expect all at once. just one step forward. note how fast everything moves since 2020, and accelerating. finally 'it's' coming...


Most people don’t operate this way. Choice is painful and induces anxiety. There’s a high chance of getting buyers remorse even if you chose the „objectively best” model.

A good salesperson will make sure the choice process is relatively quick and painless. You will feel good afterwards knowing that all the 125 aspects that differentiate this model from the other ones are not that important. The one you chose runs your favourite apps, integrates well with your car and your home entertainment system.

Understanding this and learning how to sell helps in life, incl. negotiating architectural changes with non technical decision makers.


> A good salesperson will make sure the choice process is relatively quick and painless.

The best salesperson isn't the one whose customers are leaving the shop smiling just like a TV advert where buying X or Y will solve every problem in life, but rather the one whose customers leave the shop angry after having purchased this or that product or service, because that is an indicator they were squeezed until just before the point they tell the seller to stick their product somewhere and leave for the competition. Not that I like it, but that is how I see it.


what makes you think that this is the best way to obtain loyal and more customers?


Prisoners Dilemma vs Iterated Prisoners Dilemma.

Low trust == maximize mechanical power and optimization

Higher trust == invest time, relationship-building and lower individual transaction profit over a larger volume of profit

Few consumer sales interactions fall into the second category.


prisoner’s dilemma is a dilemma for a reason: it optimizes the total outcome badly. maybe this is why the pessimization of the modern business cycle everyone loves to cry about always works out that way — we’re all interacting in a commons where trying to screw everyone else as hard as possible is the rule, not the exception.


Depends on the market of course, but scarcity, either natural or artificial, can do wonders.


This isn’t zero sum.


I don’t understand why you’re downvoted. It’s absolutely true that most people don’t like making purchasing decisions by privately comparing spec dumps, even though many programmers enjoy that.


You're telling me some people out there don't create spreadsheets and a scoring system to compare 10 different ceiling fans before purchase?


Absolutely not. It should be abstracted out enough that it can be applied to all purchases and not just ceiling fans. Otherwise, you're going to be duplicating effort for the next purchase and you don't want to have to repeat yourself.


I was actually thinking of scaling to a site first, and then expand horizontally to all ceiling-mounted products. Because what's the point if I can't monetize my decision-making system?


OK but don't you hate it when you're trying to sign up for internet service and they're like "what sorts of things do you do on the computer?"

I know what I need just gimme the 100 MBPs plan!


The author seems to ignore the fact that CSV got so popular because it is human readable. If anyone wanted a binary format there’s plenty of them - most better than this DSV.

Also, I’m on a mobile right now, so can’t verify that, but it seems the format is flawed. The reader decodes UTF8 strings after splitting the binary buffer by the delimiter, but I believe the delimiter may be a part of a UTF8 character.

Edit: just checked and there’s actually no chance that the delimiter the author chose would be part of UTF8 encoding of any other character than the delimiter itself


No, all UTF-8 multi-byte encodings have the most significant bit set.


CSV's aren't really readable either though. They're "inspectable", but that's different. So if you want to read them you'll need to either use specific software, or do some preprocessing to align things properly etc ... in which case the extra step of performing a file-wide substitution of the record separator with newlines and unit separator with tabs or sth, isn't a much worse problem.


I'd say CSVs stuck around because there weren't any other alternatives that could be easily created, appended to, read by different apps.


> The author seems to ignore the fact that CSV got so popular because it is human readable.

It might seem that way if you didn't actually read the article:

> So what’s the downside? This custom FEC tooling might give you a hint.

> For starters, it’s rather unreadable when opened in a text editor.


You wanted to make a point that time does not depend on physical location, while you chose an example that proves otherwise.

There is no absolute time in spacetime, so your calendar invite from an alien friend would include not only the coordinates on Jupiter but also a time value relative to something. Possibly Earth. Maybe even UTC, as observed on Earth.


Please don't bring relativity into this except as a fun side note. It doesn't make a meaningful difference for actual objects in space, because they all share basically the same reference frame.


The article is based only on the stats of a single freelancing site. It may be big, but it still represents only a sample of the overall market data. We do not know how big the sample is and whether it represented the same percentage of the overall market size at the beginning and end of the reported period.

Only the first conclusion listed mentions Upwork. The rest sounds like it reports a general market trend.

The author says the data was provided by a company called Revealera, but doesn’t disclose he is a co-founder. It doesn’t affect the quality of the data by itself but I’m always careful to make conclusions from data presented this way.

I visited a couple of new job ads on Upwork and I found that:

1. The „hire rate” of clients is usually between 0 and 70%.

2. Upwork has an AI solution for clients that makes it very easy to post a new job. Meaning it is easier than ever to think about an idea, post a new „job” and forget about it, never hiring anyone.


I've tried to hire artists from Upwork. Anecdotally the experience sucked. I made it clear it's for sprite sheet game assets, but it quickly got flooded by applicants who clearly never have never drawn sprite sheets.

Event worse, about 15% of portfolios had stolen artwork. (I've been around for long enough to spot obvious stolen art, but I'm not a human google image search so the real rate might be much higher than 15%)

I ended up contacting an artist that I found on itch.io directly.


Warning: you absolutely have to only allow certain countries to apply for jobs. The site works if you block India especially for most things.


> The site works if you block India especially for most things.

The site works if you don't try to get anything done by paying $5/hr to anyone. I have gotten jobs done by people from India, Serbia, and other places. I just chose sufficiently reputable freelancers and paid them what they are worth and it worked perfectly fine in all cases. There was no magical difference between freelancers from the US and freelancers from other countries in the same price ranges.


Many of the issues with Upwork came well before AI posting:

- thinking they can get Facebook built for $300 and/or sticker shock when they select "US only" freelancers

- being overwhelmed with low-quality/spammy responses (agencies copy-and-pasting, etc)

- frustration with communication barriers (whether language or time zone)

- the need to pre-pay $X to hire someone


They are conceptually different. Kafka optimizes throughput of data.

I wouldn't use Kafka for a job queue, and wouldn't use RabbitMQ for streaming data when ordering would be important.


Not (yet). This is the current list of gatekeepers and their services: https://digital-markets-act-cases.ec.europa.eu/gatekeepers


I like the walled garden of Apple as well, especially as a “family IT guy” who had no need to reset/reconfigure the systems or remove malware from any phones since talking the family members to switch to iPhones a few years back.

Some of the properties of the walled garden have nothing to do with security, though. They are simply uncompetitive practices on Apple part. I’m happy someone said “enough”.


I read this as a statement of fact. The Digital Market Act has come into force. The act gives the platforms (Apple included) few months of preparations to comply. Breton just reminds that the clock is ticking.


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