Month: May 2023

Instagram explains its recommendations and ‘shadowbanning’

Instagram is, once again, trying to explain how its recommendations work in an attempt to dispel “misconceptions” about how the app’s algorithm works and whether or not the company engages in “shadowbanning” of certain creators. In a new blog post from Instagram’s top exec Adam Mosseri, he offers one of the most detailed explanations to date on how the app ranks content in various parts of the app.
“Instagram doesn’t have a singular algorithm that oversees what people do and don’t see on the app,” Mosseri explains. Instead, he says, there are multiple algorithms and ranking systems underpinning different aspects of the app, like Explore, Reels, Stories and search. Each of these uses a variety of signals to determine how content is ranked for each user.
For example, the order of posts in your main feed is determined by your past activity, as well as previous interactions with the person who made each post. Likewise, Stories posts take into account viewing history as well as “closeness,” or “how likely you are to be connected as friends or family.” On the other hand, recommendations in Explore are largely based “posts you’ve liked, saved, shared and commented on in the past,” but are more likely to come from accounts you’ve never interacted with.
One of the more interesting sections of Mosseri’s blog post is titled “addressing shadowbanning.” Mosseri notes that there isn’t a universal definition for the word, but acknowledges that many creators “use the term to imply that a user’s account or content is limited or hidden without a clear explanation or justification.” And he says that the company is working to increase transparency around when creators’ content or accounts are blocked from the app’s recommendations.
Specifically, he calls out the app’s “account status” feature, which can alert users if one of their posts or their account is considered “ineligible” for recommendations. The feature also offers an appeals process. While it’s not the first time Instagram has addressed the issue, which has been the subject of much speculation and conspiracy theories over the years, there has been a notable shift in the way the company is talking about “shadowbanning.”
In a similar post from two years ago, Mosseri wrote that “the truth is most of your followers won’t see what you share, because most look at less than half of their Feed.” Now, he says Instagram is working on increasing transparency in cases when a creator’s content isn’t widely distributed due to a policy violation. “If anything makes your content less visible, you should know about it and be able to appeal,” he wrote.
He added that Instagram is testing “new notifications to help creators understand when the reach of their reel may be limited due to a watermark” (the company has tried to discourage users from posting recycled TikToks to Reels for years).
While some creators may still find these explanations unsatisfying — and there are more than a few who fall into that camp, judging by the comments on Mosseri’s own Instagram post — the new details underscore just how central algorithmic recommendations are becoming to Instagram. While the app re-introduced an optional chronological feed, Mark Zuckerberg has said his goal is to transform Instagram and Facebook into a “discovery engine” more focused on recommendations than posts from friends.This article originally appeared on Engadget at https://www.engadget.com/instagram-explains-its-recommendations-and-shadowbanning-234716911.html?src=rss

Instagram is, once again, trying to explain how its recommendations work in an attempt to dispel “misconceptions” about how the app’s algorithm works and whether or not the company engages in “shadowbanning” of certain creators. In a new blog post from Instagram’s top exec Adam Mosseri, he offers one of the most detailed explanations to date on how the app ranks content in various parts of the app.

“Instagram doesn’t have a singular algorithm that oversees what people do and don’t see on the app,” Mosseri explains. Instead, he says, there are multiple algorithms and ranking systems underpinning different aspects of the app, like Explore, Reels, Stories and search. Each of these uses a variety of signals to determine how content is ranked for each user.

For example, the order of posts in your main feed is determined by your past activity, as well as previous interactions with the person who made each post. Likewise, Stories posts take into account viewing history as well as “closeness,” or “how likely you are to be connected as friends or family.” On the other hand, recommendations in Explore are largely based “posts you’ve liked, saved, shared and commented on in the past,” but are more likely to come from accounts you’ve never interacted with.

One of the more interesting sections of Mosseri’s blog post is titled “addressing shadowbanning.” Mosseri notes that there isn’t a universal definition for the word, but acknowledges that many creators “use the term to imply that a user’s account or content is limited or hidden without a clear explanation or justification.” And he says that the company is working to increase transparency around when creators’ content or accounts are blocked from the app’s recommendations.

Specifically, he calls out the app’s “account status” feature, which can alert users if one of their posts or their account is considered “ineligible” for recommendations. The feature also offers an appeals process. While it’s not the first time Instagram has addressed the issue, which has been the subject of much speculation and conspiracy theories over the years, there has been a notable shift in the way the company is talking about “shadowbanning.”

In a similar post from two years ago, Mosseri wrote that “the truth is most of your followers won’t see what you share, because most look at less than half of their Feed.” Now, he says Instagram is working on increasing transparency in cases when a creator’s content isn’t widely distributed due to a policy violation. “If anything makes your content less visible, you should know about it and be able to appeal,” he wrote.

He added that Instagram is testing “new notifications to help creators understand when the reach of their reel may be limited due to a watermark” (the company has tried to discourage users from posting recycled TikToks to Reels for years).

While some creators may still find these explanations unsatisfying — and there are more than a few who fall into that camp, judging by the comments on Mosseri’s own Instagram post — the new details underscore just how central algorithmic recommendations are becoming to Instagram. While the app re-introduced an optional chronological feed, Mark Zuckerberg has said his goal is to transform Instagram and Facebook into a “discovery engine” more focused on recommendations than posts from friends.

This article originally appeared on Engadget at https://www.engadget.com/instagram-explains-its-recommendations-and-shadowbanning-234716911.html?src=rss

Read More 

6 monitor and TV innovations remind us that trade shows still exist

Provocative tech with real potential to impact future display products.

Enlarge / Samsung Display imagines its unfurling screen embodying future portable monitors. (credit: Samsung Display)

Believe it or not, technology trade shows are a thing in 2023. There are huge exceptions, like the game industry’s previously annual E3 conference. But others, like the CES consumer tech show in Las Vegas in January and the Computex computing show in Taipei this week, are still kicking and offering peeks at intriguing consumer monitor and TV tech.

No one knows what the future of tech shows holds. The pricey, flashy E3 show, for example, was declining for years before its last in-person show in 2019. Other trade shows are enduring notable decline in exhibitor numbers, in-show announcements, and attendee numbers.

This May, however, remained a time for tech trade shows. Computex started Tuesday, and The Society for Information Display (SID) held Display Week 2023 in Los Angeles last week.

As a tech reporter, the fun part of trade shows isn’t racking up steps or spotting slivers of time to eat and sleep. It’s checking out interesting products, features, and concepts that customers will soon see. It feels somewhat odd to say in this post-pandemic world, but May was actually an interesting time for trade show displays.

Read 41 remaining paragraphs | Comments

Read More 

Wall Street Firms To Take On Binance, Coinbase, Other Crypto-Native Exchanges

An anonymous reader quotes a report from CryptoSlate: Traditional financial firms, including Standard Chartered, Nomura, and Charles Schwab, are busy building or funding new crypto exchange and custody platforms, FT reported on May 31. These well-known Wall Street firms are betting that fund managers are still interested in trading crypto even after last year’s market downturn and the string of crypto scandals. The FTX bankruptcy and Terra ecosystem implosion, among others, highlighted the risk of investing through largely unregulated exchanges. But legacy firms believe asset managers prefer dealing with established players over crypto-native exchanges like Binance.

Gautam Chhugani, Senior Analyst of Global Digital Assets at Bernstein, told FT: “The large, pedigreed, traditional institutional investors definitely prefer dealing with counterparties who they know have been in existence for years and have been regulated in the traditional sense.” In a survey of 250 asset managers published by EY-Parthenon earlier this month, half of the respondents said they would consider switching from a crypto-native group to a traditional-backed company if they offered the same services. Additionally, 90% of respondents trusted traditional financial groups to act as custodians for their crypto assets.

The collapse of crypto firms last year and the disclosures on alleged malpractices eroded the trust of crypto investors. Traditional financial firms are banking on their finance industry expertise, long-standing reputations, and lack of regulatory scrutiny to attract clients. The new wave of legacy-backed crypto platforms will compete with Coinbase and Binance, which also host institutional clients. But traditional finance firms will compete by building more transparent operations — particularly in separating exchanges from asset custody to avoid conflict of interest and reduce risk. The report notes that BNY Mellon and Fidelity already operate separate crypto custody divisions. Meanwhile, the Nasdaq is waiting for regulators to greenlight its service.

Read more of this story at Slashdot.

An anonymous reader quotes a report from CryptoSlate: Traditional financial firms, including Standard Chartered, Nomura, and Charles Schwab, are busy building or funding new crypto exchange and custody platforms, FT reported on May 31. These well-known Wall Street firms are betting that fund managers are still interested in trading crypto even after last year’s market downturn and the string of crypto scandals. The FTX bankruptcy and Terra ecosystem implosion, among others, highlighted the risk of investing through largely unregulated exchanges. But legacy firms believe asset managers prefer dealing with established players over crypto-native exchanges like Binance.

Gautam Chhugani, Senior Analyst of Global Digital Assets at Bernstein, told FT: “The large, pedigreed, traditional institutional investors definitely prefer dealing with counterparties who they know have been in existence for years and have been regulated in the traditional sense.” In a survey of 250 asset managers published by EY-Parthenon earlier this month, half of the respondents said they would consider switching from a crypto-native group to a traditional-backed company if they offered the same services. Additionally, 90% of respondents trusted traditional financial groups to act as custodians for their crypto assets.

The collapse of crypto firms last year and the disclosures on alleged malpractices eroded the trust of crypto investors. Traditional financial firms are banking on their finance industry expertise, long-standing reputations, and lack of regulatory scrutiny to attract clients. The new wave of legacy-backed crypto platforms will compete with Coinbase and Binance, which also host institutional clients. But traditional finance firms will compete by building more transparent operations — particularly in separating exchanges from asset custody to avoid conflict of interest and reduce risk. The report notes that BNY Mellon and Fidelity already operate separate crypto custody divisions. Meanwhile, the Nasdaq is waiting for regulators to greenlight its service.

Read more of this story at Slashdot.

Read More 

New Desktop Macs With M2 Ultra and M2 Max Chips Could See WWDC Debut

Apple is testing two desktop Macs that are equipped with M2 Max and ‌M2‌ Ultra chips, according to Bloomberg’s Mark Gurman. The ‌M2‌ Max chip first came out in January with the launch of the 2023 14-inch and 16-inch MacBook Pro models, but the ‌M2‌ Ultra chip is new and would succeed the M1 Ultra chip that Apple uses in the Mac Studio.

Gurman does not know which specific Macs will feature the chips, but the machines are labeled as “Mac 14,13” and “Mac 14,14” internally. Previous rumors have suggested that the revamped Apple silicon Mac Pro could include the ‌M2‌ Ultra chip, the ‌Mac Pro‌ that Apple is developing is labeled as “14,8” internally, so the desktop machines in testing now are likely something else, perhaps new versions of the ‌Mac Studio‌. Apple is also working on new iMacs, but these are expected to feature M3 chips.

Back in April, Gurman said that there were updated ‌Mac Studio‌ machines planned for a future launch, but he also said that it was unlikely that Apple would release a version of the ‌Mac Studio‌ with an ‌M2‌ Ultra chip because it would be as powerful as the future ‌Mac Pro‌, giving customers little reason to opt for a ‌Mac Pro‌.

The first machine that Apple has been testing includes an ‌M2‌ Max chip with eight high-performance cores, four efficiency cores, a 30-core GPU, and 96GB RAM. The chip is the same as the chip that’s in the ‌M2‌ Max version of the 16-inch MacBook Pro.

The second machine has an ‌M2‌ Ultra chip with a 24-core CPU (16 high-performance cores and 8 efficiency cores) and a 60-core GPU, though prior information suggests that ‌M2‌ Ultra chips could feature up to a 76-core GPU. Different configurations feature 64GB, 128GB, and 192GB RAM.

Apple is testing these new Macs just ahead of WWDC, and Gurman says that he expects multiple Macs to be introduced at the event. One of those will be the 15-inch MacBook Air, but we don’t know which other Macs might appear. Gurman stops short of suggesting these new Macs with ‌M2‌ Max and ‌M2‌ Ultra chips will be introduced at WWDC, but it seems like a distinct possibility.Related Roundup: WWDC 2023

Related Forum: Apple, Inc and Tech Industry

This article, “New Desktop Macs With M2 Ultra and M2 Max Chips Could See WWDC Debut” first appeared on MacRumors.comDiscuss this article in our forums

Apple is testing two desktop Macs that are equipped with M2 Max and ‌M2‌ Ultra chips, according to Bloomberg‘s Mark Gurman. The ‌M2‌ Max chip first came out in January with the launch of the 2023 14-inch and 16-inch MacBook Pro models, but the ‌M2‌ Ultra chip is new and would succeed the M1 Ultra chip that Apple uses in the Mac Studio.

Gurman does not know which specific Macs will feature the chips, but the machines are labeled as “Mac 14,13” and “Mac 14,14” internally. Previous rumors have suggested that the revamped Apple silicon Mac Pro could include the ‌M2‌ Ultra chip, the ‌Mac Pro‌ that Apple is developing is labeled as “14,8” internally, so the desktop machines in testing now are likely something else, perhaps new versions of the ‌Mac Studio‌. Apple is also working on new iMacs, but these are expected to feature M3 chips.

Back in April, Gurman said that there were updated ‌Mac Studio‌ machines planned for a future launch, but he also said that it was unlikely that Apple would release a version of the ‌Mac Studio‌ with an ‌M2‌ Ultra chip because it would be as powerful as the future ‌Mac Pro‌, giving customers little reason to opt for a ‌Mac Pro‌.

The first machine that Apple has been testing includes an ‌M2‌ Max chip with eight high-performance cores, four efficiency cores, a 30-core GPU, and 96GB RAM. The chip is the same as the chip that’s in the ‌M2‌ Max version of the 16-inch MacBook Pro.

The second machine has an ‌M2‌ Ultra chip with a 24-core CPU (16 high-performance cores and 8 efficiency cores) and a 60-core GPU, though prior information suggests that ‌M2‌ Ultra chips could feature up to a 76-core GPU. Different configurations feature 64GB, 128GB, and 192GB RAM.

Apple is testing these new Macs just ahead of WWDC, and Gurman says that he expects multiple Macs to be introduced at the event. One of those will be the 15-inch MacBook Air, but we don’t know which other Macs might appear. Gurman stops short of suggesting these new Macs with ‌M2‌ Max and ‌M2‌ Ultra chips will be introduced at WWDC, but it seems like a distinct possibility.

Related Roundup: WWDC 2023

This article, “New Desktop Macs With M2 Ultra and M2 Max Chips Could See WWDC Debut” first appeared on MacRumors.com

Discuss this article in our forums

Read More 

AI: War crimes evidence erased by social media platforms

Footage of potential human rights abuses may be lost after platforms delete it, the BBC has found.

Footage of potential human rights abuses may be lost after platforms delete it, the BBC has found.

Read More 

Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding

Photonic computing startup Lightmatter is taking its big shot at the rapidly growing AI computation market with a hardware-software combo it claims will help the industry level up — and save a lot of electricity to boot. Lightmatter’s chips basically use optical flow to solve computational processes like matrix vector products. This math is at
Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding by Devin Coldewey originally published on TechCrunch

Photonic computing startup Lightmatter is taking its big shot at the rapidly growing AI computation market with a hardware-software combo it claims will help the industry level up — and save a lot of electricity to boot.

Lightmatter’s chips basically use optical flow to solve computational processes like matrix vector products. This math is at the heart of a lot of AI work, and currently performed by GPUs and TPUs that specialize in it, but use traditional silicon gates and transistors.

The issue with those is that we’re approaching the limits of density and therefore speed for a given wattage or size. Advances are still being made, but at great cost and pushing the edges of classical physics. The supercomputers that make training models like GPT-4 possible are enormous, consume huge amounts of power, and produce a lot of waste heat.

“The biggest companies in the world are hitting an energy power wall and experiencing massive challenges with AI scalability. Traditional chips push the boundaries of what’s possible to cool, and data centers produce increasingly large energy footprints. AI advances will slow significantly unless we deploy a new solution in data centers,” said Lightmatter CEO and founder Nick Harris.

Some have projected that training a single large language model can take more energy than 100 U.S. homes consume in a year. Additionally, there are estimates that 10-20 percent of the world’s total power will go to AI inference by the end of the decade unless new compute paradigms are created.”

Lightmatter, of course, intends to be one of those new paradigms. Its approach is, at least potentially, faster and more efficient, using arrays of microscopic optical waveguides let the light essentially perform logic operations just by passing through them: a sort of analog-digital hybrid. Since the waveguides are passive, the main power draw is creating the light itself, then reading and handling the output.

One really interesting aspect of this form of optical computing is that you can increase the power of the chip just by using more than one color at once. Blue does one operation while red does another — though in practice it’s more like 800 nanometers wavelength does one, 820 does another. It’s not trivial to do so, of course, but these “virtual chips” can vastly increase the amount of computation done on the array. Twice the colors, twice the power.

Harris started the company based on optical computing work he and his team did at MIT (which is licensing the relevant patents to them), and managed to wrangle an $11 million seed round back in 2018. One investor said then that “this isn’t a science project,” but Harris admitted in 2021 that while they knew “in principle” the tech should work, there was a hell of a lot to do to make it operational. Fortunately, he was telling me that in the context of investors dropping a further $80 million on the company.

Now Lightmatter has raised a $154 million C round and is preparing for its actual debut. It has several pilots going with its full stack of Envise (computing hardware), Passage (interconnect, crucial for large computing operations), and Idiom, a software platform that Harris says should let machine learning developers adapt quickly.

A Lightmatter Envise unit in captivity.

“We’ve built a software stack that integrates seamlessly with PyTorch and TensorFlow. The workflow for machine learning developers is the same from there – we take the neural networks built in these industry standard applications and import our libraries, so all the code runs on Envise,” he explained.

The company declined to make any specific claims about speedups or efficiency improvements, and because it’s a different architecture and computing method it’s hard to make apples-to-apples comparisons. But we’re definitely talking along the lines of an order of magnitude, not a measly 10 or 15 percent. Interconnect is similarly upgraded, since it’s useless to have that level of processing isolated on one board.

Of course, this is not the kind of general-purpose chip that you could use in your laptop; it’s highly specific to this task. But it’s the lack of task specificity at this scale that seems to be holding back AI development — though “holding back” is the wrong term since it’s moving at great speed. But that development is hugely costly and unwieldy.

The pilots are in beta, and mass production is planned for 2024, at which point presumably they ought to have enough feedback and maturity to deploy in data centers.

The funding for this round came from SIP Global, Fidelity Management & Research Company, Viking Global Investors, GV, HPE Pathfinder, and existing investors.

Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding by Devin Coldewey originally published on TechCrunch

Read More 

Scroll to top
Generated by Feedzy