The newspaper of record did it again, revived the lab leak hypothesis with a stupid opinion piece that is light on the evidence and heavy on the presuppositions. This is not helpful. We already have a popular bias that is contrary to the science, so this is just fueling more error.

The origin controversy is political and polarized. Myths that COVID-19 was somehow a manmade pandemic are still impactful, whether they are true or not. Polls have shown that 2 out of 3 US citizens believe that SARS-CoV-2, the virus that started the COVID-19 pandemic, came out of a laboratory rather than nature.

Scientists worldwide vehemently disagree. The emerging scientific consensus among domain experts is that SARS-CoV-2 is a natural virus that entered humanity via zoonotic spillover (more importantly, there is a consensus stemming from the body of evidence that is entirely unequivocal).

Thanks, NY Times, for boosting a conspiracy theory over the evidence.

The article was written by Alina Chan, who previously coauthored a book on the topic with Matt Ridley. Ridley is, unfortunately, a bit of a loon on many topics, including climate change as well as the lab leak hypothesis, and I guess he’s infectious, because Chan has got it bad. Their book, Viral, was terrible.

The lab leak theory, for the uninitiated, is the notion that the Covid-19 virus that has now devastated the globe is not of purely natural origin but rather escaped from a lab after it was harvested from the wild or engineered by Chinese scientists. It’s not actually a single theory but, rather, a grab bag of possible scenarios by which the virus might have been unleashed on the world—all of them implying some level of shady or incompetent behavior by Chinese scientists. And in trying to take each of these scenarios seriously, Viral’s authors have unintentionally exposed the entire farce of the lab leak discourse—showing both the exceptional flimsiness of the lab leakers’ narrative and also why this very flimsiness makes the lab leak conspiracy theory so hard to eradicate. By relying on an ever-growing arsenal of seemingly suspicious facts, each pointing in a slightly different direction, lab leaker discourse renders itself completely unfalsifiable.

If you want a brief, straightforward rebuttal of Alina Chan’s editorial, Larry Moran has you covered.

Alina Chan has five reasons why the scientists at the Wuhan Institute of Virology were working on SARS-Cov-2 before the pandemic began and why they are denying that the virus escaped from their lab. All of these five points have been discredited and/or discounted but that didn’t stop the newspaper from promoting them.

1. The SARS-like virus that caused the pandemic emerged in Wuhan, the city where the world’s foremost research lab for SARS-like viruses is located.
This is just about the only thing in the lab leak conspiracy theory that is true.

2. The year before the outbreak, the Wuhan institute, working with U.S. partners, had proposed creating viruses with SARS‑CoV‑2’s defining feature.

This is extremely misleading. The researchers at WIV worked in collaboration with scientists in other countries, including the United States, on investigating the features of coronaviruses that could lead to infection of humans. That’s exactly what you would expect them to do. They never created a virus that could be infectious.

3. The Wuhan lab pursued this type of work under low biosafety conditions that could not have contained an airborne virus as infectious as SARS‑CoV‑2.

The labs followed all the standard procedures for work of this type and passed an international inspection.

4. The hypothesis that Covid-19 came from an animal at the Huanan Seafood Market in Wuhan is not supported by strong evidence.

That’s a lie. There is strong evidence that the outbreak began in the market.

5. Key evidence that would be expected if the virus had emerged from the wildlife trade is still missing.

It’s true that the exact infectious animal carrying SARS-CoV-2 has not been identified but the circumstantial evidence is strong—just as strong as the circumstantial evidence that sends some people to jail. It’s crazy to say that evidence for animal transmission is missing when ALL the evidence for the presence of SARS-CoV-2 at WIT is also missing.

I don’t understand why the lab leak hypothesis is popular at all, but I suspect it’s because most people are uncomfortable with the idea that natural processes can produce surprising effects in the absence of intent. It’s the same bias that drives creationism.

The Neuralink device has been implanted in one (1) person, Noland Arbaugh, so far. It’s not going well.

An estimated 85-percent of Neuralink’s brain-computer interface (BCI) implant threads connected to the first human patient’s motor cortex are now completely detached and his brain has shifted inside his skull up to three times what the company expected, volunteer Noland Arbaugh told The Wall Street Journal on Monday. Arbaugh also stated Neuralink has since remedied the initial performance issues using an over-the-air software update and is performing better than before, but the latest details continue to highlight concerns surrounding the company’s controversial, repeatedly delayed human implant study.

Neuralink’s coin-sized N1 BCI implant’s 64 wires thinner than a human hair are inserted a few millimeters into the motor cortex. Each thread contains 16 electrodes that translate a user’s neural activity into computer commands like typing and cursor movement. Around 870 of the 1024 electrodes in Arbaugh’s implant are no longer functional—an issue that allegedly took Neuralink a “few weeks” to remedy, reports The WSJ. When Arbaugh asked if his implant could be removed, fixed, or even replaced, Neuralink’s medical team relayed they would prefer to avoid another brain surgery and instead gather more information.

That device was inserted in January. In less than 6 months, it has decayed to 15% functionality, and the surgical team is reluctant to repair connectivity. That’s understandable; if the implant has basically torn out of place and built up scar tissue, there’s no point to sticking a second batch of wires into the same damaged spot, and relocating it to a new location is just going to tear up a different patch of Arbaugh’s brain.

The perils of being the first: you get to experience all the unforeseen problems, and also render yourself unsuitable for the Mark II device.

Oh well, too bad. Moving on, Neuralink is asking to stick wires in the brain of a second volunteer/guinea pig/sucker. There is no shortage of quadraplegics lined up for a miracle, and I can’t blame them.

The U.S. health regulator has allowed billionaire Elon Musk’s Neuralink to implant its brain chip in a second person after it proposed to fix a problem that occurred in its first patient, the Wall Street Journal reported on Monday.
Earlier this month, Neuralink said tiny wires implanted in the brain of its first patient had pulled out of position. Reuters reported last week, citing sources, the company knew from animal testing that the wires might retract.
The company intends to fix the problem by embedding some of the device’s wires deeper into the brain, the WSJ report said citing a person familiar with the company and a document it had viewed.

That last line is terrifying. Drill deeper! Get those wires in there, lock ’em in place, so if they do shift, they’ll rip up even more cortex! We better hope the second subject doesn’t know anything about the fate of the first.

This isn’t their only approach, though. They’re also thinking of patching the software. One of their goals is that Neuralink should be a discreet implant — I recall doing chronic implants in cats, where we’d get just one electrode in place, and lock it down with steel screws in the skull and great lumps of pink dental acrylic holding it down — which is obviously unsuitable for a human. So they have to make a small, low-profile device that operates on tiny voltages, and that also transmits and receives data to a larger, more capable computer. That’s a big constraint. Neuralink has put out a call for better algorithms, ones capable of a 200:1 lossless data compression with minimal computing power.

Turning brain signals into computer inputs means transmitting a lot of data very quickly. A problem for Neuralink is that the implant generates about 200 times more brain data per second than it can currently wirelessly transmit. Now, the company is seeking a new algorithm that can transmit this data in a smaller package — a process called compression — through a public challenge.

As a barebones web page announcing the Neuralink Compression Challenge posted on Thursday explains, “[greater than] 200x compression is needed.” The winning solution must also run in real time, and at low power.

Crucially, it specifies that the compression must be “lossless.” A “lossy” compression would be like a low-quality MP3 file, compared to pristine vinyl.

I know smart people are reading this blog. How about it? Get to work and write a revolutionary lossless compression algorithm that is capable of 200:1 reduction. I’m not a computer programmer anymore, so I’ll have to pass on the challenge, but I’m sure someone out there can do it…especially for such a great reward!

The reward for developing this miraculous leap forward in technology? A job interview, according to Neuralink employee Bliss Chapman. There is no mention of monetary compensation on the web page.

Although, to be fair, if you can write an efficient, fast 200:1 lossless compression algorithm, you can probably find better employment prospects than an Elon Musk company.

Also, there might be other reasons that Neuralink has invented what looks to be a hopeless task. They actually want the effort to fail.

Observers on social media immediately branded the task “impossible,” even speculating that Neuralink staff launched the challenge as a way of convincing the infamously incalcitrant Musk that it couldn’t be done.

A paper in the journal Pharmaceutics, Inhaled Medicines for Targeting Non-Small Cell Lung Cancer by Arwa Omar Al Khatib, Mohamed El-Tanani, and Hisham Al-Obaidi, might be good science, but it’s so far outside my field that I’m not equipped to judge. There are little things that I would have taken a red pen to — the first sentence of the abstract starts, “Throughout the years…” which is vague and clumsy and useless, but OK, we can’t expect literary excellence in everything some nerd writes — which put me on edge, but nothing to obviously indict it as a poor bit of work. That is, until I saw the figure.

Wow. What a glorious splortch of utterly useless visual noise. Is the whole paper an equivalent pile of machine-processed nonsense?

I really am wondering what the authors were thinking. Why would you insert a vivid technicolor example of obviously meaningless garbage into the middle of your work? Because you can? It really calls into question the validity of the text, and it makes the journal look like a rinky-tink circus sideshow. Where were the reviewers? The editors? Non small cell lung cancer is a serious concern — imagine a patient researching their disease, and seeing that doctors see their organs as exploding balls of orange and blue, like the contents of a SF movie poster.

You’d think if there were anything AI could get right, it would be science and coding. It’s just code itself, right? Although I guess that’s a bit like expecting humans to all be master barbecue chefs because they’re made of meat.

Unfortunately, AI is really good at confabulation — they’re just engines for making stuff up. And that leads to problems like this:

Several big businesses have published source code that incorporates a software package previously hallucinated by generative AI.

Not only that but someone, having spotted this reoccurring hallucination, had turned that made-up dependency into a real one, which was subsequently downloaded and installed thousands of times by developers as a result of the AI’s bad advice, we’ve learned. If the package was laced with actual malware, rather than being a benign test, the results could have been disastrous.

Wait, programmers are asking software to write their code for them? My programming days are long behind me, in a time when you didn’t have many online sources with complete code segments written for us, so you couldn’t be that lazy. We also had to write our code in a blizzard, while hiking uphill.

There’s another problem: AIs are getting their information from publicly available texts written by humans on the internet, and those are the people you should never trust. Here’s a simple question someone asked: how many years did it take to form a layer of sediment that I see in cliffs? It’s an awkward sort of question of the kind a naive layman might ask, but the computer bravely tried to find an answer.

No, the “traditional view of sedimentary layers” is not being challenged. It is not being replaced by a “biblical view.” You can hardly blame the software for being stupid, though, because look at its sources: the Institute for Creation Research and Answers in Genesis. Bullshit in, bullshit out.

Here we go again. Another paper, this time in Radiology Case Reports, got published while including obvious AI-generated text. I haven’t read the paper, since it’s been pulled, but it’s easy to see where it went wrong.

It begins:

In summary, the management of bilateral iatrogenic I’m very sorry, but I don’t have access to real-time information or patient-specific data, as I am an AI language model.

That is enraging. The author of this paper is churning them out so heedlessly that they provide no time or care to the point they’ve given up writing and now have given up reading their own work. Back in the day when I was publishing with coauthors, we were meticulous to the point of tedium in proofreading — we’d have long sessions where we’d read alternate sentences of the paper to each other to catch any typos and review the content. Ever since I’ve assumed that most authors follow some variation of that procedure. I was wrong.

If I knew an author was this sloppy and lazy in their work, I wouldn’t trust anything they ever wrote. How can you make all the thought and effort you put into the science, and then just hand off the communication of that science to an unthinking machine? It suggests to me that as little thought was put into the research as in the writing.

No wonder there is such a glut of scientific literature.