Humans Need Not Apply

[robinson]

Actually a few people did point out the blog sounded like it was written by a bot

[robinson]

Those people were mocked by the people who were fooled

[robinson]

Which sort of sums up the human condition

[Witness]

Face restoration from old pictures:



If you want to know how it works:

[Witness]

AI confirms 50 new planets from old NASA data, in a groundbreaking first

Machine learning holds promise for making sense out of heaps of possible planet sightings.

Our planet-hunting telescopes have gotten so good at their jobs that they've located thousands of possible planets outside our solar system. That means scientists have to sift through a whole lot of data to figure out what's a real planet and what's a pretender.

A research team led by David Armstrong at the University of Warwick in the UK has worked out how to harness artificial intelligence to handle some of the heavy-lifting of planet confirmation, giving astronomers a new tool to help validate distant worlds.

Telescopes like NASA's Transiting Exoplanet Survey Satellite (TESS) look for a telltale dip in brightness that indicates something is passing by a star. Sometimes this is a planet, sometimes it's a glitch, asteroids, dust or a quirk of a binary star system.

The research team created a machine learning algorithm and trained it using data on confirmed planets and false-positives from NASA's retired Kepler mission. Then they turned it loose to analyze a group of unconfirmed planet candidates, also from the Kepler data. In a first, the AI system confirmed 50 planets out of that bunch.

"The algorithm we have developed lets us take 50 candidates across the threshold for planet validation, upgrading them to real planets," Armstrong said in a Warwick release Tuesday. Validating planets can help scientists direct their resources to interesting spots in space without wasting their time on "fake" planets.

https://www.cnet.com/news/ai-confirms-5 ... ing-first/

[Witness]

Elon Musk says Neuralink will be like a ‘Fitbit in your skull with tiny wires’

The world finally got a close look at the current state of Elon Musk’s Neuralink project, courtesy of a live demo Friday evening. The demo showed a new look for the device, a peek at the robot that would install it in a person’s brain — and a pig with stage fright.

What is the Neuralink? What does it do?

As Musk explained, many neurological problems that people experience — such as memory loss, depression, blindness, and seizures, to name a few — are the result of electrical signals on the brain firing improperly. The Neuralink is an implant that directly interfaces with a person’s brain, reading signals from the brain, and even altering them to fix problems.

It’s essentially a “Fitbit in your skull with tiny wires,” Musk explained.

The original concept for the Neuralink, which we detailed for you in 2017, was a chip positioned behind the ear, with threads extending into the skull. The design has changed significantly, and the device now resembles a small coin.

According to Musk, to install a Neuralink, a tiny piece of your skull is removed and the Neuralink is slotted in, where it will sit flush with the skull (no electronics jutting out). Electrical threads about 1/20th the thickness of hair extend into the brain where they can pick up or manipulate electrical signals.

For many potential Neuralink users, undergoing brain surgery might make them uneasy, but the company is not just building the chip, but also a robot to install it. The robot will ideally handle the most difficult aspects of the surgery, which Neuralink hopes will take under an hour and be done without general anesthesia.

The device has “all-day” battery life, and can be recharged without cords.

https://www.digitaltrends.com/news/neur ... date-2020/ for the rest (demonstrated on pigs).

So ads in your head 24/7?

[Anaxagoras]

Elon Musk says Neuralink will be like a ‘Fitbit in your skull with tiny wires’

So Elon Musk wants to implant a chip in your brain?


Seriously though, it sounds like maybe someday it might lead to something interesting.

Of course this has also been a topic in science fiction going back to at least Philip K. Dick.

Will someone agree to be the first human guinea pig? Because research on pigs and other animals may be of limited usefulness.

Will we someday be able to have all of the functions of a smartphone (both good and bad) in a brain implant?

Maybe it will allow people to be punished for having "illicit thoughts"

The ultimate tool of Big Brother? Or conversely, an "upgrade" to humanity? I know there are some people who can't wait for the cyborg future to arrive.

[robinson]

More than likely we will see people hooking this shit up to the pleasure centers, and clicking the button until they die in their chair

[robinson]

That’s the story I was thinking of

[Anaxagoras]

More than likely we will see people hooking this shit up to the pleasure centers, and clicking the button until they die in their chair

Yeah, just imagine. Seriously, people will fuck themselves up if you can use it to get high.

[Witness]

↑ A dearth of guinea pigs? You know some people will do anything to be "different".

---

Machine-Generated Knowledge Bases

Human-generated knowledge bases like Wikipedia have a recall problem. First, there are the articles that should be there but are entirely missing. The unknown unknowns.

...

We are publicly releasing free-licensed data about scientists that we’ve been generating along the way, starting with 30,000 computer scientists. Only 15% of them are known to Wikipedia. The data set includes 1 million news sentences that quote or describe the scientists, metadata for the source articles, a mapping to their published work in the Semantic Scholar Open Research Corpus, and mappings to their Wikipedia and Wikidata entries. We will revise and add to that data as we go. (Many thanks to Oren Etzioni and AI2 for data and feedback.) Our aim is to help the open data research community build better tools for maintaining Wikipedia and Wikidata, starting with scientific content.

We trained Quicksilver’s models on 30,000 English Wikipedia articles about scientists, their Wikidata entries, and over 3 million sentences from news documents describing them and their work. Then we fed in the names and affiliations of 200,000 authors of scientific papers.

In the morning we found 40,000 people missing from Wikipedia who have a similar distribution of news coverage as those who do have articles. Quicksilver doubled the number of scientists potentially eligible for a Wikipedia article overnight.

It also revealed the second flavor of the recall problem that plagues human-generated knowledge bases: information decay. For most of those 30,000 scientists who are on English Wikipedia, Quicksilver identified relevant information that was missing from their articles.

Creating an article for a person is only the start. It must be maintained forever, updated as the world changes. The vast majority of information on Wikipedia is known to be correct and well cited, even after more than a decade of stunts and studies to prove otherwise. But as Fetahu et al. showed last year, Wikipedia lags significantly behind news about people and events.

https://primer.ai/blog/quicksilver for details.

[Grammatron]

[robinson]

Yeah, until somebody shits all over the men’s room

[Witness]

Amazon warehouses that employ robots have 50 PERCENT more serious injuries than all-human facilities, new report reveals

• A new report accuses Amazon of hiding a 'mounting injury crisis'
• Serious injuries at fulfillment centers are nearly twice the industry norm
• Facilities with robots have even higher rates due to increased production goals
• Amazon insists the high numbers are due to the firm encouraging employees to report even minor injuries

https://www.dailymail.co.uk/sciencetech ... thout.html

[Rob Lister]

Amazon warehouses that employ robots have 50 PERCENT more serious injuries than all-human facilities, new report reveals

• A new report accuses Amazon of hiding a 'mounting injury crisis'
• Serious injuries at fulfillment centers are nearly twice the industry norm
• Facilities with robots have even higher rates due to increased production goals
• Amazon insists the high numbers are due to the firm encouraging employees to report even minor injuries

https://www.dailymail.co.uk/sciencetech ... thout.html

From the article,

Today, Amazon uses more than 200,000 robotic vehicles, called 'drives,' in dozens of its 175 fulfillment centers.

That can't be even close to right. It is the Daily Fail but that still, that's not even trying to be credible. I might believe 200. Hell, I might believe 1000.

[Witness]

From the article,

Today, Amazon uses more than 200,000 robotic vehicles, called 'drives,' in dozens of its 175 fulfillment centers.

That can't be even close to right. It is the Daily Fail but that still, that's not even trying to be credible. I might believe 200. Hell, I might believe 1000.

According to Business Insider, 45,000 as of January 2017 with a 50% yearly increase: https://www.businessinsider.in/Amazon-n ... 315471.cms

45,000 * 1.5⁴ ~ 230,000.

[Witness]

How many human employees?

https://www.google.com/

[robinson]

Robots can’t file lawsuits

[robinson]

Yet

[Witness]

Long article, perhaps interesting to history buffs (excerpts, evidently):

Fake video threatens to rewrite history. Here’s how to protect it

AI-generated deepfakes aren’t just a problem for politics and other current affairs. Unless we act now, they could also tamper with our record of the past.

Since deepfakes burst onto the scene a few years ago, many have worried that they represent a grave threat to our social fabric. Creators of deepfakes use artificial intelligence-based neural network algorithms to craft increasingly convincing forgeries of video, audio, and photography almost as if by magic. But this new technology doesn’t just threaten our present discourse. Soon, AI-generated synthetic media may reach into the past and sow doubt into the authenticity of historical events, potentially destroying the credibility of records left behind in our present digital era.

In an age of very little institutional trust, without a firm historical context that future historians and the public can rely on to authenticate digital media events of the past, we may be looking at the dawn of a new era of civilization: post-history. We need to act now to ensure the continuity of history without stifling the creative potential of these new AI tools.
...
This is the age of post-history: a new epoch of civilization where the historical record is so full of fabrication and noise that it becomes effectively meaningless. It’s as if a cultural singularity ripped a hole so deeply in history that no truth can emerge unscathed on the other side.
...
Without reliable digital primary source documents—and without an ironclad chronology in which to frame both the documents and their digital context—the future study of the history of this period will be hampered dramatically, if not completely destroyed.

Potential solutions

• Maintain better historical archives
• Train computers to spot fakes
• Call in the moderators
• Authenticate trustworthy content
• Create a universal timestamp
• Restrict access to deepfake tools
• Build a cryptographic ark for the future

https://www.fastcompany.com/90549441/ho ... -deepfakes

[Rob Lister]

Long article, perhaps interesting to history buffs (excerpts, evidently):

Fake video threatens to rewrite history. Here’s how to protect it

https://www.fastcompany.com/90549441/ho ... -deepfakes

The whole article is well worth the read.

[Witness]

U.S. government agencies to use AI to cull and cut outdated regulations

(This Oct 16 story restores dropped words in first paragraph to say tens of thousands of pages, not tens of pages; corrects fourth paragraph to say 185,000 pages remaining, not published annually)

WASHINGTON (Reuters) - The White House Office of Management and Budget (OMB) said Friday that federal agencies will use artificial intelligence to eliminate outdated, obsolete, and inconsistent requirements across tens of thousands of pages of government regulations.

A 2019 pilot project used machine learning algorithms and natural language processing at the Department of Health and Human Services. The test run found hundreds of technical errors and outdated requirements in agency rulebooks, including requests to submit materials by fax.

OMB said all federal agencies are being encouraged to update regulations using AI and several agencies have already agreed to do so.

Over the last four years, the number of pages in the Code of Federal Regulations has remained at about 185,000.

White House OMB director Russell Vought said the AI effort would help agencies “update a regulatory code marked by decades of neglect and lack of reform.”

https://www.reuters.com/article/us-usa- ... SKBN27130L

Big scale Turing test: will the AIs sneak in some self-serving rules?

[robinson]

Of course









But it won’t be the AI actually doing it

[robinson]

Lela chess zero (Google deep mind)

Continues to astound chess masters and players worldwide

Everything we thought we knew about chess was wrong

[robinson]

Lela crushes the best chess engines, and continues to come up with winning moves in games that were thought to be well understood

They use known openings for the first moves, then let her do her thing

It doesn’t take long for new moves to show up, and stunning victories follow

It’s fucking truly mind blowing

[robinson]

Oh, and yeah, humans need not apply

A human has no chance of winning

[Witness]

A portrait of Jesus "reconstructed" with some AI. Details here: https://twitter.com/ganbrood/status/130 ... 03/photo/1

[Rob Lister]

There are now businesses that sell fake people. On the website Generated.Photos, you can buy a “unique, worry-free” fake person for $2.99, or 1,000 people for $1,000. If you just need a couple of fake people — for characters in a video game, or to make your company website appear more diverse — you can get their photos for free on ThisPersonDoesNotExist.com. Adjust their likeness as needed; make them old or young or the ethnicity of your choosing. If you want your fake person animated, a company called Rosebud.AI can do that and can even make them talk.

https://www.nytimes.com/interactive/202 ... faces.html

I recommend clicking the link. There's some cool html going on there.

ETA: all of there examples are beautiful people; there are no ugly ones. That might be a flaw

Oh, and

[robinson]

Finally, my dream has come true

[Anaxagoras]

[robinson]

[Anaxagoras]

Virtual Influencers Make Real Money While Covid Locks Down Human Stars

What is a 'virtual influencer'? An AI-created persona used to advertise products on social media. The social media 'influencer' market is $15 billion and growing.

Imma has nearly 300,000 Instagram followers and has partnered with Ferragamo; she’s shot editorials with fashion magazines. She’s not real.

Virtual influencers were already gaining, well, influence long before Covid-19 struck.
Seraphine’s flowing pink hair and cat-themed Instagram posts had attracted thousands of fans when the news that she was created by Riot Games Inc. — the studio behind smash-hit esports game League of Legends — sent her account viral. Now her follower count is nearly 400,000 and she’s making appearances in Shanghai to promote her music, while most flesh-and-blood social-media stars are stuck at home. Despite not being real, she still sometimes wears a mask.

At a time when interacting safely with other humans can no longer be taken for granted, the appetite for digital spokespeople is accelerating. Brands are expected to spend as much as $15 billion annually on influencer marketing by 2022, up from $8 billion last year, according to Business Insider Intelligence. A growing slice of that money belongs to virtual influencers, and traditional marketing is experiencing serious disruption.
“Virtual influencers, while fake, have real business potential,” says Christopher Travers, the founder of virtualhumans.org, a website that documents the industry. “They are cheaper to work with than humans in the long term, are 100% controllable, can appear in many places at once, and, most importantly, they never age or die.”

Seraphine — who on Oct. 13 was also revealed to be a playable character on League of Legends, which draws as many as 8 million concurrent daily users — is one of about 125 active virtual influencers, according to Travers. More than 50 of those debuted on social media in the 18 months to June 2020. On YouTube, virtual influencers number more than 5,000.
Digital avatars developed by creative agencies, the biggest influencers can attract brand partnerships and other lucrative deals. With 2.8 million social-media followers and a fee of about $8,500 per sponsored post, Lil Miquela — a “model” who’s done promotions for Calvin Klein, Prada and other fashion brands — is the industry’s highest earner, according to OnBuy, a U.K.-based online marketplace. OnBuy estimates Lil Miquela will make about $11.7 million for her creators this year. As Covid-19 leads to the cancellation of product launches and sponsored travel, some human influencers are seeing revenue streams dry up. Meanwhile Lil Miquela recently debuted a music video at this year’s online-only Lollapalooza festival.

I wonder if someday our artificial overlords will have avatars like these?

[robinson]

William Gibson predicted this, wrote about this, it's in his book Virtual Light

If you haven't read it (and I know you have not), you might enjoy the fuck out of it

[robinson]

It's part of a trilogy

[Pyrrho]

[Witness]

Uh, oh, we're doomed (again): Calculations Show It'll Be Impossible to Control a Super-Intelligent AI

Excerpt:

"A super-intelligence poses a fundamentally different problem than those typically studied under the banner of 'robot ethics'," write the researchers.

"This is because a superintelligence is multi-faceted, and therefore potentially capable of mobilising a diversity of resources in order to achieve objectives that are potentially incomprehensible to humans, let alone controllable."

Spoiler:

[Witness]

Facial recognition reveals political party in troubling new research

Researchers have created a machine learning system that they claim can determine a person’s political party, with reasonable accuracy, based only on their face. The study, from a group that also showed that sexual preference can seemingly be inferred this way, candidly addresses and carefully avoids the pitfalls of “modern phrenology,” leading to the uncomfortable conclusion that our appearance may express more personal information that we think.

The study, which appeared this week in the Nature journal Scientific Reports, was conducted by Stanford University’s Michal Kosinski. Kosinski made headlines in 2017 with work that found that a person’s sexual preference could be predicted from facial data.

The study drew criticism not so much for its methods but for the very idea that something that’s notionally non-physical could be detected this way. But Kosinski’s work, as he explained then and afterwards, was done specifically to challenge those assumptions and was as surprising and disturbing to him as it was to others. The idea was not to build a kind of AI gaydar — quite the opposite, in fact. As the team wrote at the time, it was necessary to publish in order to warn others that such a thing may be built by people whose interests went beyond the academic:

We were really disturbed by these results and spent much time considering whether they should be made public at all. We did not want to enable the very risks that we are warning against. The ability to control when and to whom to reveal one’s sexual orientation is crucial not only for one’s well-being, but also for one’s safety.

We felt that there is an urgent need to make policymakers and LGBTQ communities aware of the risks that they are facing. We did not create a privacy-invading tool, but rather showed that basic and widely used methods pose serious privacy threats.

Similar warnings may be sounded here, for while political affiliation at least in the U.S. (and at least at present) is not as sensitive or personal an element as sexual preference, it is still sensitive and personal. A week hardly passes without reading of some political or religious “dissident” or another being arrested or killed. If oppressive regimes could obtain what passes for probable cause by saying “the algorithm flagged you as a possible extremist,” instead of for example intercepting messages, it makes this sort of practice that much easier and more scalable.

The algorithm itself is not some hyper-advanced technology. Kosinski’s paper describes a fairly ordinary process of feeding a machine learning system images of more than a million faces, collected from dating sites in the U.S., Canada and the U.K., as well as American Facebook users. The people whose faces were used identified as politically conservative or liberal as part of the site’s questionnaire.

https://techcrunch.com/2021/01/13/facia ... -research/