This appears to be almost like a SPAC. Allbirds had already sold it's IP and other assets, now they raised new money and are continuing under a different name but they're still a publicly traded company.
So it's not really shoe retailer pivots to AI but a shoe retailer selling all assets and forming a new company but uses the previous public stock listing.
This would be my bet - filing for an IPO or even direct listing is months of SEC review, audits, underwriters, due diligence, etc. A shell with an existing ticker gets you access to that sweet retail investor cash almost immediately, and with less of those pesky regulators asking if you actually have a functioning product or company.
This is more akin to a reverse merger than a SPAC (eg. Berkshire Hathaway being a failing textile mill and WPP being a wire basket company) except it is unusual to see it happen within an existing leadership team. They sold off all their IP so figured they might as well use the shell to try and cash in on AI hype, I guess.
Can you explain to me how this isn't considered outright fraud? The SEC has rules specifically around the lifetime of a company / ticket in terms of things like inclusion in indexes and retirement accounts, right?
How does allowing this not simply encourage a world of, basically, stock market karma farming: making bullshit barely company companies, just to sell the ticket so they can be used to engage in a pump and dump scheme with the little wealth the working class has left?
It is not my field either except for amateur interest. My understanding is that because they are publicly disclosing it to investors, it's not fraud in the legal sense. Fraud requires deception. It could be that they do genuinely believe that their expertise in shoe selling translates to expertise in AI infra.
If you agree (or think that enough people will agree to increase the value of the stock), you can buy the shares. If you don't, you aren't forced to buy it - and as a penny stock with a market cap of $21MM, nobody's index fund or pension is going to be forced to buy it either.
The stock market sort of _is_ just karma farming - building belief in your company vision so that investors bring capital. Nearly all companies trade at a positive "P/E ratio" - that is, the price of a share is on average 10-20X higher than their current earnings - the difference representing pure belief that the company will earn more in the future.
The regulatory guardrails around it are not perfect, but striking the balance between allowing the public to participate in the growth of successful companies in a dynamic economy, and protecting them from scams, is a fine line. Being able to invest in publicly traded companies has made many middle class and working class people wealthy, the regulations do work for most people to keep them out of trouble while allowing them to participate. The people who get hurt are the ones who trade penny stocks like lottery tickets, which is less a regulatory failure and more the impulsive behavior that drives any kind of gambling.
> The company, valued at around $4 billion at its peak, sold its intellectual property and other assets two weeks ago for $39 million.
...used the ticker to build stock hype that will bring in another $50M:
> The company, which according to the release will be called NewBird AI, announced a deal to raise up to $50 million in funding, expected to close in the second quarter of 2026.
...and is planning on using that $90M of capital to sell a few extra shovels to the marginal buyer in the latest hype market.
> “The Company will initially seek to acquire high-performance, low-latency AI compute hardware and provide access under long-term lease arrangements, meeting customer demand that spot markets and hyperscalers are unable to reliably service,” the company said in the announcement.
This is really just picking the corpse clean... company lost 99% of value, dropping from $4B to $0.04B. This is just redirecting what little capital is left into something that might get a small return for whoever is left holding shares.
Just to add a little bit of nuance to this not because I'm trying to defend GitHub, they definitely need to up their reliability, but the 90% uptime figure represents every single service that GitHub offers being online 90% of the time. You don't need every single service to be online in order to use GitHub. For example, I don't use Copilot myself and it's seen a 96.47% uptime, the worst of the services which are tracked.
That’s… one 9 of reliability. You could argue the title understates the problem.
> You don't need every single service to be online in order to use GitHub.
Well that’s how they want you to use it, so it’s an epic failure in their intended use story. Another way to put this is ”if you use more GitHub features, your overall reliability goes down significantly and unpredictably”.
Look, I have never been obsessed with nines for most types of services. But the cloud service providers certainly were using it as major selling/bragging points until it got boring and old because of LLMs. Same with security. And GitHub is so upstream that downstream effects can propagate and cascade quite seriously.
On the other hand: it also doesn't include instances where GitHub is painfully slow but technically usable.
These days it is very common that something like opening the diff view of a trivial PR takes 15-30 seconds to load. Sure, it will eventually load after a long wait or an F5, but it is still negatively impacting my productivity.
There have been multiple outages in the past year where they didn’t even fully report it very quickly. I’m talking the types of outages that brings down normal enterprise usage: we hook delivery for CI/CD, git operations for everyone, PRs for code review. And that’s not even including GitHub actions or copilot which lots of people also rely on.
Not sure if I fully understand it, but this seems highly inefficient?
Instead of using embeddings which are easy to make a cheap to compare, you use summarized sections of documents and process them with an LLM? LLM's are slower and more expensive to run.
If this is used as an important tool call for an AI agent that preforms many other calls, then it's likely that the added cost and latency would be negligible compared to the benefit of significantly improved retrieval. As an analogy, for a small task you're often ok with just going over the first few search results, but to prepare for a large project, you might want to spend an afternoon researching.
In specific domains, accuracy matters more than than speed. Document structure and reasoning bring better retrieval than semantic search which retrieves "similar" but not "relevant" results.
The idea this person is trying for is a LLM that explores the codebase using the source graph in the way a human might, by control+clicking in idea/vscode to go to definition, searching for usages of a function, etc. It actually does work, other systems use it as well, though they have the main agent performing the codebase walk rather than delegate to a "codebase walker" agent.
My concern would be that a function called setup() might mask some really important thing, likewise a “preface” chapter might get missed by an LLM when you ask some specially deep question.
Either way that your input data structure could build bad summaries that the LLM misses with.
I think it only needs to generate the tree once before retrieval, and it doesn’t require any external model at query time. The indexing may take some time upfront, but retrieval is then very fast and cost-free.
For better diarization quality than pyannote, check out Whisper-DiarizationX which combines Whisper with ECAPA-TDNN speaker embeddings and spectral clustering.
I've experienced this as well. I'm working on a project for which I wanted to search through transcripts of a video. This is often a very long text. I figured since models like the GPT 4.1 series have very large context windows RAG was not needed but I definitely notice some strange issues, especially on the smaller models. Things like not answering the question that was asked but returning a generic summary of the content.
To be fair (or pedantic), in this post they didn't have root, so cat'ing etc/passwd would not have been possible, whereas installing a doom apk is trivial.
So it's not really shoe retailer pivots to AI but a shoe retailer selling all assets and forming a new company but uses the previous public stock listing.