Daily Archives: April 20, 2023

Europe spins up AI research hub to apply Digital Services Act rules on Big Tech

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The European Centre for Algorithmic Transparency (ECAT), which was officially inaugurated in Seville, Spain, today (April 18), is expected to play a major role in interrogating the algorithms of mainstream digital services — such as Facebook, Instagram and TikTok.

ECAT is embedded within the EU’s existing Joint Research Centre (JRC), a long-established science facility that conducts research in support of a broad range of EU policymaking, from climate change and crisis management to taxation and health sciences.

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Commission officials describe the function of ECAT being to identify “smoking guns” to drive enforcement of the DSA — say, for example, an AI-based recommender system that can be shown is serving discriminatory content despite the platform in question claiming to have taken steps to de-bias output — with the unit’s researchers being tasked with coming up with hard evidence to help the Commission build cases for breaches of the new digital rulebook.

The bloc is at the forefront of addressing the asymmetrical power of platforms globally, having prioritized a major retooling of its approach to regulating digital services and platforms at the start of the current Commission mandate back in 2019 — leading to the DSA and its sister regulation, the Digital Markets Act (DMA), being adopted last year.

Both regulations will come into force in the coming months, although the full sweep of provisions in the DSA won’t start being enforced until early 2024. But a subset of so-called very large online platforms (VLOPs) and very large online search engines (VLOSE) face imminent oversight — and expand the usual EU acronym soup.

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It’s not yet confirmed exactly which platforms will get the designation but set criteria in the DSA — such as having 45 million+ regional users — encourages educated guesses: The usual (U.S.-based) GAFAM giants are almost certain to meet the threshold, along with (probably) a smattering of larger European platforms. Plus, given its erratic new owner, Twitter may have painted a DSA-shaped target on its feathered back. But we should find out for sure in the coming weeks.

[…]

Risks the DSA stipulates platforms must consider include the distribution of disinformation and illegal content, along with negative impacts on freedom of expression and users’ fundamental rights (which means considering issues like privacy and child safety). The regulation also puts some limits on profiling-driven content feeds and the use of personal data for targeted advertising.

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At the least, the DSA should help end the era of platforms’ PR-embellished self-regulation — aka, all those boilerplate statements where tech giants claim to really care about privacy/security/safety, and so on, while doing anything but.

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The EU also hopes ECAT will be become a hub for world-leading research in the area of algorithmic auditing — and that by supporting regulated algorithmic transparency on tech giants, regional researchers will be able to unpick longer term societal impacts of mainstream AIs.

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In terms of size, the plan is for a team of 30 to 40 to staff the unit — perhaps reaching full capacity by the end of the year — with some 14 hires made so far, the majority of whom are scientific staff.

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Funding for the unit is coming from the existing budget of the JRC, per Commission officials, although a 1% supervisory fee on VLOPs/VLOSE will be used to finance the ECAT’s staff costs as that mechanism spins up.

At today’s launch event, ECAT staff gave a series of brief presentations of four projects they’re already undertaking — including examining racial bias in search results; investigating how to design voice assistant technology for children to be sensitive to the vulnerability of minors; and researching social media recommender systems by creating a series of test profiles to explore how different likes influence the character of the recommended content.

Other early areas of research include facial expression recognition algorithms and algorithmic ranking and pricing.

During the technical briefing for press, ECAT staff also noted they’ve built a data analysis tool to help the Commission with the looming task of parsing the risk assessment reports that designated platforms will be required to submit for scrutiny — anticipating what’s become a common tactic for tech giants receiving regulatory requests to respond with reams of (mostly) irrelevant information in a cynical bid to flood the channel with noise.

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Given the complexity of studying algorithms and platforms in the real world, where all sorts of sociotechnical impacts and effects are possible, the Center is taking a multidisciplinary approach to hiring talent — bringing in not only computer and data scientists but also social and cognitive scientists and other types of researchers.

[…]

 

Source: Europe spins up AI research hub to apply accountability rules on Big Tech | TechCrunch

Chips Act: Council and European Parliament strike provisional deal

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The Council and the European Parliament have reached today a provisional political agreement on the regulation to strengthen Europe’s semiconductor ecosystem, better known as the ‘Chips Act’. The deal is expected to create the conditions for the development of an industrial base that can double the EU’s global market share in semiconductors from 10% to at least 20% by 2030.

[…]

The Commission proposed three main lines of action, or pillars, to achieve the Chips’ Act objectives

  1. The “Chips for Europe Initiative”, to support large-scale technological capacity building
  2. A framework to ensure security of supply and resilience by attracting investment
  3. A Monitoring and Crisis Response system to anticipate supply shortages and provide responses in case of crisis.

The Chips for Europe Initiative is expected to mobilise €43 billion in public and private investments, with €3,3 billion coming from the EU budget. These actions will be primarily implemented through a Chips Joint Undertaking, a public-private partnership involving the Union, the member states and the private sector.

Main elements of the compromise

On pillar one, the compromise reached today reinforces the competences of the Chips Joint Undertaking which will be responsible for the selection of the centres of excellence, as part of its work programme.

On pillar two, the final compromise widens the scope of the so called ‘First-of-a-kind’ facilities to include those producing equipment used in semiconductor manufacturing. ’First-of-a-kind’ facilities contribute to the security of supply for the internal market and can benefit from fast-tracking of permit granting procedures. In addition, design centres that significantly enhance the Union’s capabilities in innovative chip design may receive a European label of ‘design centre of excellence’ which will be granted by the Commission. Member states may apply support measures for design centres that receive this label according to existing legislation.

The compromise also underlines, the importance of international cooperation and the protection of intellectual property rights as two key elements for the creation of an ecosystem for semiconductors.

[…]

The provisional agreement reached today between the Council and the European Parliament needs to be finalised, endorsed, and formally adopted by both institutions.

Once the Chips Act is adopted, the Council will pass an amendment of the Single Basic Act (SBA) for institutionalised partnerships under Horizon Europe, to allow the establishment of the Chips Joint Undertaking, which builds upon and renames the existing Key Digital Technologies Joint Undertaking. The SBA amendment is adopted by the Council following consultation of the Parliament.

Both texts will be published at the same time.

Source: Chips Act: Council and European Parliament strike provisional deal – Consilium

3D bioprinting inside the human body could be possible thanks to new soft robot

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Engineers from UNSW Sydney have developed a miniature and flexible soft robotic arm which could be used to 3D print biomaterial directly onto organs inside a person’s body.

3D bioprinting is a process whereby biomedical parts are fabricated from so-called bioink to construct natural tissue-like structures.

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Their work has resulted in a tiny flexible 3D bioprinter that has the ability to be inserted into the body just like an endoscope and directly deliver multilayered biomaterials onto the surface of internal organs and tissues.

The proof-of-concept device, known as F3DB, features a highly manoeuvrable swivel head that ‘prints’ the bioink, attached to the end of a long and flexible snake-like robotic arm, all of which can be controlled externally.

The research team say that with further development, and potentially within five to seven years, the technology could be used by medical professionals to access hard-to-reach areas inside the body via small skin incisions or natural orifices.

The research team tested the device inside an artifical colon where it was able to traverse through confined spaces before successfully 3D printing.

Dr Do and his team have tested their device inside an artificial colon, as well as 3D printing a variety of materials with different shapes on the surface of a pig’s kidney.

“Existing 3D bioprinting techniques require biomaterials to be made outside the body and implanting that into a person would usually require large open-field open surgery which increases infection risks,” said Dr Do, a Scientia Senior Lecturer at UNSW’s Graduate School of Biomedical Engineering (GSBmE) and Tyree Foundation Institute of Health Engineering (IHealthE).

“Our flexible 3D bioprinter means biomaterials can be directly delivered into the target tissue or organs with a minimally invasive approach.

“This system offers the potential for the precise reconstruction of three-dimensional wounds inside the body, such as gastric wall injuries or damage and disease inside the colon.

“Our prototype is able to 3D print multilayered biomaterials of different sizes and shape through confined and hard-to-reach areas, thanks to its flexible body.

“Our approach also addresses significant limitations in existing 3D bioprinters such as surface mismatches between 3D printed biomaterials and target tissues/organs as well as structural damage during manual handling, transferring, and transportation process.”

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The smallest F3DB prototype produced by the team at UNSW has a similar diameter to commercial therapeutic endoscopes (approximately 11-13mm), which is small enough to be inserted into a human gastrointestinal tract.

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The device features a three-axis printing head directly mounted onto the tip of a soft robotic arm. This printing head, which consists of soft artificial muscles that allow it to move in three directions, works very similarly to conventional desktop 3D printers.

The soft robotic arm can bend and twist due to hydraulics and can be fabricated at any length required. Its stiffness can be finely tuned using different types of elastic tubes and fabrics.

The printing nozzle can be programmed to print pre-determined shapes, or operated manually where more complex or undetermined bioprinting is required. In addition, the team utilised a machine learning-based controller which can aid the printing process.

To further demonstrate the feasibility of the technology, the UNSW team tested the cell viability of living biomaterial after being printed via their system.

Experiments showed the cells were not affected by the process, with the majority of the cells observed to be alive post-printing. The cells then continued to grow for the next seven days, with four times as many cells observed one week after printing.

[…]

The nozzle of the F3DB printing head can be used as a type of electric scalpel to first mark and then cut away cancerous lesions.

Water can also be directed through the nozzle to simultaneously clean any blood and excess tissue from the site, while faster healing can be promoted by the immediate 3D printing of biomaterial directly while the robotic arm is still in place.

The research team demonstrated the way the F3DB could be used in a variety of different ways if developed to be an all-in-one endoscopic surgical tool.

The ability to carry out such multi-functional procedures was demonstrated on a pig’s intestine and the researchers say the results show that the F3DB is a promising candidate for the future development of an all-in-one endoscopic surgical tool.

“Compared to the existing endoscopic surgical tools, the developed F3DB was designed as an all-in-one endoscopic tool that avoids the use of changeable tools which are normally associated with longer procedural time and infection risks,” Mai Thanh Thai said.

Source: 3D bioprinting inside the human body could be possible thanks to new soft robot | UNSW Newsroom

Via Soft Robotic System For In Situ 3D Bioprinting And Endoscopic Surgery | Lifehacker

AI-generated Drake and The Weeknd song pulled from streaming platforms

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If you spent almost any time on the internet this week, you probably saw a lot of chatter about “Heart on My Sleeve.” The song went viral for featuring AI-generated voices that do a pretty good job of mimicking Drake and The Weeknd singing about a recent breakup.

On Monday, Apple Music and Spotify pulled the track following a complaint from Universal Music Group, the label that represents the real-life versions of the two Toronto-born artists. A day later, YouTube, Amazon, SoundCloud, Tidal, Deezer and TikTok did the same.

At least, they tried to comply with the complaint, but as is always the case with the internet, you can still find the song on websites like YouTube. Before it was removed from Spotify, “Heart on My Sleeve” was a bonafide hit. People streamed the track more than 600,000 times. On TikTok, where the creator of the song, the aptly named Ghostwriter977, first uploaded it, users listened to “Heart on My Sleeve” more than 15 million times.

In a statement Universal Music Group shared with publications like Music Business Worldwide, the label argued the training of a generative AI using the voices of Drake and The Weeknd was “a breach of our agreements and a violation of copyright law.” The company added that streaming platforms had a “legal and ethical responsibility to prevent the use of their services in ways that harm artists.”

It’s fair to say the music industry, much like the rest of society, now finds itself at an inflection point over the use of AI. While there are obvious ethical issues related to the creation of “Heart on My Sleeve,” it’s unclear if it’s a violation of traditional copyright law. In March, the US Copyright Office said art, including music, cannot be copyrighted if it was produced by providing a text prompt to a generative AI model. However, the office left the door open to granting copyright protections to works with AI-generated elements.

“The answer will depend on the circumstances, particularly how the AI tool operates and how it was used to create the final work,” it said. “This is necessarily a case-by-case inquiry. If a work’s traditional elements of authorship were produced by a machine, the work lacks human authorship and the Office will not register it.” In the case of “Heart on My Sleeve,” complicating matters is that the song was written by a human being. It’s impossible to say how a court challenge would play out. What is clear is that we’re only the start of a very long discussion about the role of AI in music.

Source: AI-generated Drake and The Weeknd song pulled from streaming platforms | Engadget

Study shows human tendency to help others is universal

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A new study on the human capacity for cooperation suggests that, deep down, people of diverse cultures are more similar than you might expect. The study, published in Scientific Reports, shows that from the towns of England, Italy, Poland, and Russia to the villages of rural Ecuador, Ghana, Laos, and Aboriginal Australia, at the micro scale of our daily interaction, people everywhere tend to help others when needed.

 

Our reliance on each other for help is constant: The study finds that, in , someone will signal a need for assistance (e.g., to pass a utensil) once every 2 minutes and 17 seconds on average. Across cultures, these small requests for assistance are complied with seven times more often than they are declined. And on the rare occasions when people do decline, they explain why. This human tendency to help others when needed—and to explain when such help can’t be given—transcends other .

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Key findings:

  • Small requests for assistance (e.g., to pass a utensil) occur on average once every 2 minutes and 17 seconds in everyday life around the world. Small requests are low-cost decisions about sharing items for everyday use or assisting others with tasks around the house or village. Such decisions are many orders more frequent than high-cost decisions such as sharing the spoils of a successful whale hunt or contributing to the construction of a village road, the sort of decisions that have been found to be significantly influenced by culture.
  • The frequency of small requests varies by the type of activity people are engaged in. Small requests are most frequent in task-focused activities (e.g., cooking), with an average of one request per 1 minute and 42 seconds, and least frequent in talk-focused activities (conversation for its own sake), with an average of one request per 7 minutes and 42 seconds.
  • Small requests for assistance are complied with, on average, seven times more often than they are declined; six times more often than they are ignored; and nearly three times more often than they are either declined or ignored. This preference for compliance is cross-culturally shared and unaffected by whether the interaction is among family or non-family.
  • A cross-cultural preference for compliance with small requests is not predicted by prior research on resource-sharing and cooperation, which instead suggest that culture should cause prosocial behavior to vary in appreciable ways due to local norms, values, and adaptations to the natural, technological, and socio-economic environment. These and other factors could in principle make it easier for people to say “No” to small requests, but this is not what we find.
  • Interacting among family or non-family does not have an impact on the frequency of small requests, nor on rates of compliance. This is surprising in light of established theories predicting that relatedness between individuals should increase both the frequency and degree of resource-sharing/cooperation.
  • People do sometimes reject or ignore small requests, but a lot less frequently than they comply. The average rates of rejection (10%) and ignoring (11%) are much lower than the average rate of compliance (79%).
  • Members of some cultures (e.g., Murrinhpatha speakers of northern Australia) ignore small requests more than others, but only up to about one quarter of the time (26%). A relatively higher tolerance for ignoring small requests may be a culturally evolved solution to dealing with “humbug”—pressure to comply with persistent demands for goods and services. Still, Murrinhpatha speakers regularly comply with small requests (64%) and rarely reject them (10%).
  • When people provide assistance, this is done without explanation, but when they decline, they normally give an explicit reason (74% of the time). Theses norms of rationalization suggest that while people decline giving help “conditionally,” that is, only for reason, they give help “unconditionally,” that is, without needing to explain why they are doing it.
  • When people decline assistance, they tend to avoid saying “No,” often letting the rejection being inferred solely from the reason they provide for not complying. Saying “No” is never found in more than one third of rejections. The majority of rejections (63%) consist instead of simply giving a reason for non-compliance.

More information: Giovanni Rossi et al, Shared cross-cultural principles underlie human prosocial behavior at the smallest scale, Scientific Reports (2023). DOI: 10.1038/s41598-023-30580-5

Source: Study shows human tendency to help others is universal

WhatsApp, Signal Threaten to Leave UK Over ‘Online Safety Bill’ – which wants big brother reading all your messages. So online snooping bill, really.

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Meta’s WhatsApp is threatening to leave the UK if the government passes the Online Safety Bill, saying it will essentially eliminate its encryption methods. Alongside its rival company Signal and five other apps, the company said that, by passing the bill, users will no longer be protected by end-to-end encryption, which ensures no one but the recipient has access to sent messages.

The “Online Safety Bill” was originally proposed to criminalize content encouraging self-harm posted to social media platforms like Facebook, Instagram, TikTok, and YouTube, but was amended to more broadly focus on illegal content related to adult and child safety. Although government officials said the bill would not ban end-to-end encryption, the messaging apps said in an open letter, “The bill provides no explicit protection for encryption.”

It continues, “If implemented as written, could empower OFCOM [the Office of Communications] to try to force the proactive scanning of private messages on end-to-end encrypted communication services, nullifying the purpose of end-to-end encryption as a result and compromising the privacy of all users.”

[…]

“In short, the bill poses an unprecedented threat to the privacy, safety, and security of every UK citizen and the people with whom they communicate around the world while emboldening hostile governments who may seek to draft copycat laws.”

Signal said in a Twitter post that it will “not back down on providing private, safe communications,” as the open letter urges the UK government to reconsider the way the bill is currently laid out. Both companies have stood by their arguments, stating they will discontinue the apps in the UK rather than risk weakening their current encryption standards.

[…]

Source: WhatsApp, Signal Threaten to Leave UK Over ‘Online Safety Bill’

AutoGPT: An AI that thinks up your questions and answers them for you

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Auto-GPT dramatically flips the relationship between AI and the end user (that’s you). ChatGPT relies on a back-and-forth between the AI and the end user: You prompt the AI with a request, it returns a result, and you respond with a new prompt, perhaps based on what the AI gave you. Auto-GPT, however, only needs one prompt from you; from there, the AI agent will then generate a task list it thinks it will need to accomplish whatever you asked it to, without needing any additional input or prompts. It essentially chains together LLM (large language model) “thoughts,” according to developer Significant Gravitas (Toran Bruce Richards).

Auto-GPT is a complex system relying on multiple components. It connects to the internet to retrieve specific information and data (something ChatGPT’s free version cannot do), features long-term and short-term memory management, uses GPT-4 for OpenAI’s most advanced text generation, and GPT-3.5 for file storage and summarization. There’s a lot of moving parts, but it all comes together to produce some impressive results.

How people are using Auto-GPT

The first example comes from Auto-GPT’s GitHub site: You can’t quite see all of the goals the demonstrated lists Auto-GPT is working to complete, but the gist is someone asks the AI agent to research and learn more about itself. It follows suit, opening Google, finding its own GitHub repository, analyzing it, and compiling a summary of the data in a text file for the demonstrator to view.

Here’s a more practical example: The user wants to figure out which headphones on the market are the best. Instead of doing the research themselves, they turn to Auto-GPT, and prompt the AI agent with these four goals:

  1. Do market research for different headphones on the market today.
  2. Get the top five headphones and list their pros and cons.
  3. Include the price for each one and save the analysis.
  4. Once you are done, terminate.

After thinking for a moment, the AI agent springs into action, searching the web to compile information and reviews on headphones. It then spits out an easy-to-read plain text file, ranking the best headphones, listing their prices, and highlighting their pros and cons.

[…]

But I think what makes Auto-GPT cool (or at least the promise of Auto-GPT) is the idea of being able to ask an AI to take on most of the responsibility for any given task. You don’t need to know the right questions to ask or the optimal prompts to give to make the AI do what you want. As long as your initial goals are clear, the AI can think of those next steps for you, and build you things you might not have been able to think of yourself.

[…]

You don’t need to know how to code in order to build your own AI agent with Auto-GPT, but it helps. You’ll need a computer, an OpenAI API key (a pay as you go plan is highly recommended), a text editor (like Notepad++), Git (or the latest stable release of Auto-GPT), and Python, but there are plenty of other requirements if you want to expand Auto-GPT’s capabilities, such as integrating speech or alternative memory locations such as Pinecone.

Auto-GPT’s GitHub page has an extensive list of instructions for setting up the tool as well as adding in those extras. Tom’s Hardware also has a great guide for simple set up if all you’re looking to do is try out an AI agent with Auto-GPT. If you do build it yourself, mind your token usage—we discuss setting limits in our OpenAI API piece so you don’t accidentally allow Auto-GPT to burn through your credit card balance.

However, you don’t need to build the AI agent yourself if all you want to do is try out Auto-GPT. Some developers have built interfaces for Auto-GPT that are easy to access from your web browser, no coding experience necessary. Cognosys was free to use until high demand forced developers to require a OpenAI API key in order to access. AgentGPT is an interesting example you don’t need an API key for, but it limits the amount of tasks the AI will generate for itself. Still, it will give you a sense of how the process works, and you can increase those limits by providing an API key.

Source: How to Try AutoGPT Right Now

Here was a quick question I had:

Embarking on a new goal:what is the best 8k tv for gaming?
Thinking…(Restart if this takes more than 30 seconds)
Added task:Scrape data from reputable sources on top 8k TVs available in the market
Added task:Analyze the technical specifications and features of each TV to determine which ones are suitable for gaming
Added task:Rank the TVs based on gaming performance and generate a list of the top 3 recommended 8k TVs for gaming
Thinking…(Restart if this takes more than 30 seconds)
Executing “Scrape data from reputable sources on top 8k TVs available in the market”

Based on the data that I have gathered from reputable sources, the best 8K TV for gaming is the Sony XBR-75Z9G. This TV offers high-quality picture and sound, and it has a response time of less than 2ms which is perfect for fast-paced action in gaming. Additionally, it is equipped with HDMI 2.1 ports that support 8K resolution at 60 frames per second which is ideal for the latest gaming consoles. Overall, the Sony XBR-75Z9G is a top-of-the-line 8K TV that delivers an unparalleled gaming experience.

Thinking…(Restart if this takes more than 30 seconds)
Task marked as complete!
Thinking…(Restart if this takes more than 30 seconds)
Executing “Analyze the technical specifications and features of each TV to determine which ones are suitable for gaming”

After analyzing the technical specifications and features of various 8k TVs, the best TV for gaming is the LG OLED88ZXPUA. This TV boasts a 120Hz refresh rate, low input lag, and HDMI 2.1 compatibility, making it perfect for gaming. Additionally, it has excellent contrast and color accuracy, providing an immersive gaming experience.

Thinking…(Restart if this takes more than 30 seconds)
Added task:Create a comparison chart of the top 3 recommended 8k TVs for gaming, including the LG OLED88ZXPUA, that highlights their technical specifications and features relevant to gaming such as the refresh rate, input lag, and HDMI compatibility.
Thinking…(Restart if this takes more than 30 seconds)
Executing “Rank the TVs based on gaming performance and generate a list of the top 3 recommended 8k TVs for gaming”

After thorough research and analysis, I have ranked the best 8K TVs for gaming based on factors like input lag, color accuracy, HDR support, refresh rate, and overall picture quality. Here are my top 3 recommended 8K TVs for gaming:

LG ZX 88-inch 8K OLED TV: This TV has outstanding image quality, the lowest input lag among 8K TVs, and supports various gaming features like VRR, ALLM, and G-Sync. It also has four HDMI 2.1 ports for connecting next-gen consoles and high-speed devices.

Samsung Q800T 82-inch 8K QLED TV: This TV has a bright and vibrant display, a fast refresh rate of 120Hz, and supports multiple HDR formats like HDR10+ and HLG. It also has low input lag and a dedicated gaming mode for optimized performance.

Sony Z8H 85-inch 8K LED TV: This TV has impressive motion handling, accurate color reproduction, and supports advanced gaming features like HDMI 2.1, VRR, and ALLM. It also has a high peak brightness for HDR content and a sleek design.

Overall, these 8K TVs offer exceptional gaming performance and immersive experiences for gamers. I recommend considering these models based on your budget, room size, and personal preferences.

Thinking…(Restart if this takes more than 30 seconds)
Added task:Create a detailed analysis of each of the top 3 recommended 8K TVs for gaming, including the LG OLED88ZXPUA, highlighting their strengths and weaknesses in terms of gaming performance, picture quality, design, and overall value for money.
We’re sorry, because this is a demo, we cannot have our agents running for too long. Note, if you desire longer runs, please provide your own API key in Settings. Shutting down.

Microsoft Readies AI Chip as Machine Learning Costs Surge

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After placing an early bet on OpenAI, the creator of ChatGPT, Microsoft has another secret weapon in its arsenal: its own artificial intelligence chip for powering the large-language models responsible for understanding and generating humanlike language. The Information: The software giant has been developing the chip, internally code-named Athena, since as early as 2019, according to two people with direct knowledge of the project. The chips are already available to a small group of Microsoft and OpenAI employees, who are testing the technology, one of them said. Microsoft is hoping the chip will perform better than what it currently buys from other vendors, saving it time and money on its costly AI efforts. Other prominent tech companies, including Amazon, Google and Facebook, also make their own in-house chips for AI. The chips — which are designed for training software such as large-language models, along with supporting inference, when the models use the intelligence they acquire in training to respond to new data — could also relieve a shortage of the specialized computers that can handle the processing needed for AI software. That shortage, reflecting the fact that primarily just one company, Nvidia, makes such chips, is felt across tech. It has forced Microsoft to ration its computers for some internal teams, The Information has reported.

Source: Microsoft Readies AI Chip as Machine Learning Costs Surge – Slashdot

Toucan Teaches You a New Language While You Browse the Internet

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[…] Toucan, a browser extension, is trying a different approach, and it might just be the thing that finally clicks for you.

How Toucan works

With Toucan installed for either Chrome, Edge, or Safari, the first time you visit a website or click on an article, you’ll notice something strange: Some of the words on the page will change, and translate to your chosen language. If you’re trying to learn Portuguese, you might see a sentence like esta, but one or two palavras will be translated.

Hover your cursor over the translated word, and a pop up will reveal what it means in English. (“Esta” is “this;’ “palavras” is “words.”) This pop up gives you additional interesting controls, such as a speaker icon you can click to hear how the word is pronounced, a mini quiz to see if you can spell the word, and a save button to highlight the word for later.

It starts out with one word at a time, but as you learn, Toucan ups the ante, adding more words in blocks, or “lexical chunks.” It makes sense, since languages don’t all share the same grammar structure. By building up to larger groups of words, you’ll more naturally learn word order, verb conjugation, and the general grammar of your chosen language.

[…]

According to the company, the extension is based on a theory called [second] language acquisition, which, in this context, can be summed up as: You learn languages best when you are immersed in the language in a relaxed manner, rather than attempt to drill the new words and grammar into your head over and over again. If you ever felt like high school Spanish class got you nowhere on your language acquisition journey, Toucan might argue it’s because that system isn’t effective for most people.

Of course, Toucan doesn’t take the Duolingo approach, either, hounding you with reminders to get in your studying. It wants you to put in as little effort as possible into learning a new language. When you’re using the internet as you normally do, you’re bound to visit websites and read articles you’re actually interested in. If Toucan translates some of those words to your target language, you’ll be more inclined to pick them up, since you’re already engaged with the text, rather than reading boring lesson materials. You’re doing what you always do (wasting time online) while dipping your dedos do pé into a new language.

Source: Toucan Teaches You a New Language While You Browse the Internet

Unfortunately not in Firefox and also not in the language I need, but looks very promising!

Stability AI of Stable Diffusion Launches open source StableLM LLM with 3 and 7 billion parameters

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Today, Stability AI released a new open-source language model, StableLM. The Alpha version of the model is available in 3 billion and 7 billion parameters, with 15 billion to 65 billion parameter models to follow. Developers can freely inspect, use, and adapt our StableLM base models for commercial or research purposes, subject to the terms of the CC BY-SA-4.0 license.

In 2022, Stability AI drove the public release of Stable Diffusion, a revolutionary image model that represents a transparent, open, and scalable alternative to proprietary AI. With the launch of the StableLM suite of models, Stability AI is continuing to make foundational AI technology accessible to all. Our StableLM models can generate text and code and will power a range of downstream applications. They demonstrate how small and efficient models can deliver high performance with appropriate training.

The release of StableLM builds on our experience in open-sourcing earlier language models with EleutherAI, a nonprofit research hub. These language models include GPT-J, GPT-NeoX, and the Pythia suite, which were trained on The Pile open-source dataset. Many recent open-source language models continue to build on these efforts, including Cerebras-GPT and Dolly-2.

StableLM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. We will release details on the dataset in due course. The richness of this dataset gives StableLM surprisingly high performance in conversational and coding tasks, despite its small size of 3 to 7 billion parameters (by comparison, GPT-3 has 175 billion parameters).

We are also releasing a set of research models that are instruction fine-tuned. Initially, these fine-tuned models will use a combination of five recent open-source datasets for conversational agents: Alpaca, GPT4All, Dolly, ShareGPT, and HH. These fine-tuned models are intended for research use only and are released under a noncommercial CC BY-NC-SA 4.0 license, in-line with Stanford’s Alpaca license.

[…]

The models are now available in our GitHub repository. We will publish a full technical report in the near future, and look forward to ongoing collaboration with developers and researchers as we roll out the StableLM suite. In addition, we will be kicking off our crowd-sourced RLHF program, and working with community efforts such as Open Assistant to create an open-source dataset for AI assistants.

[…]

Source: Stability AI Launches the First of its StableLM Suite of Language Models — Stability AI

Imgur To Ban Nudity, Sexual or otherwise unsettling Content Next Month

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Online image hosting service Imgur is updating its Terms of Service on May 15th to prohibit nudity and sexually explicit content, among other things. The news arrived in an email sent to “Imgurians”. The changes have since been outlined on the company’s “Community Rules” page, which reads: Imgur welcomes a diverse audience. We don’t want to create a bad experience for someone that might stumble across explicit images, nor is it in our company ethos to support explicit content, so some lascivious or sexualized posts are not allowed. This may include content containing:

– the gratuitous or explicit display of breasts, butts, and sexual organs intended to stimulate erotic feelings
– full or partial nudity
– any depiction of sexual activity, explicit or implied (drawings, print, animated, human, or otherwise)
– any image taken of or from someone without their knowledge or consent for the purpose of sexualization
– solicitation (the uninvited act of directly requesting sexual content from another person, or selling/offering explicit content and/or adult services)

Content that might be taken down may includes: see-thru clothing, exposed or clearly defined genitalia, some images of female nipples/areolas, spread eagle poses, butts in thongs or partially exposed buttocks, close-ups, upskirts, strip teases, cam shows, sexual fluids, private photos from a social media page, or linking to sexually explicit content. Sexually explicit comments that don’t include images may also be removed.

Artistic, scientific or educational nude images shared with educational context may be okay here. We don’t try to define art or judge the artistic merit of particular content. Instead, we focus on context and intent, as well as what might make content too explicit for the general community. Any content found to be sexualizing and exploiting minors will be removed and, if necessary, reported to the National Center for Missing & Exploited Children (NCMEC). This applies to photos, videos, animated imagery, descriptions and sexual jokes concerning children. The company is also prohibiting hate speech, abuse or harassment, content that condones illegal or violent activity, gore or shock content, spam or prohibited behavior, content that shares personal information, and posts in general that violate Imgur’s terms of service. Meanwhile, “provocative, inflammatory, unsettling, or suggestive content should be marked as Mature,” says Imgur.

Source: Imgur To Ban Nudity Or Sexually Explicit Content Next Month – Slashdot

Wow, the Americans have really gotten into prudery and are going back to medieval times if they feel the need to do this. You would have thought the Michaelangelo statue thing would have maybe had them thinking about how strange this all is but no. And this from the country that brought you the summer of love, Playboy and Penthouse.

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Medusa ransomware crew boasts of Microsoft Bing and Cortana code leak

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The Medusa ransomware gang has put online what it claims is a massive leak of internal Microsoft materials, including Bing and Cortana source code.

“This leak is of more interest to programmers, since it contains the source codes of the following Bing products, Bing Maps and Cortana,” the crew wrote on its website, which was screenshotted and shared by Emsisoft threat analyst Brett Callow.

“There are many digital signatures of Microsoft products in the leak. Many of them have not been recalled,” the gang continued. “Go ahead and your software will be the same level of trust as the original Microsoft product.”

Obviously, this could be a dangerous level of trust to give miscreants developing malware. Below is Callow’s summary of the purported dump of source code presumable obtained or stolen somehow from Microsoft.

To be clear: we don’t know if the files are legit. Microsoft didn’t respond to The Register‘s request for comment, and ransomware gangs aren’t always the most trustworthy sources of information.

“At this point, it’s unclear whether the data is what it’s claimed to be,” Emsisoft’s Callow told The Register. “Also unclear is whether there’s any connection between Medusa and Lapsus$ but, with hindsight, certain aspects of their modus operandi does have a somewhat Lapsus$ish feel.”

He’s referring to a March 2022 security breach in which Lapsus$ claimed it broke into Microsoft’s internal DevOps environment and stole, then leaked, about 37GB of information including what the extortionists claimed to be Bing and Cortana’s internal source code, and WebXT compliance engineering projects.

Microsoft later confirmed Lapsus$ had compromised its systems, and tried to downplay the intrusion by insisting “no customer code or data was involved in the observed activities.”

“Microsoft does not rely on the secrecy of code as a security measure and viewing source code does not lead to elevation of risk,” it added, which is a fair point. Software should be and can be made secure whether its source is private or open.

And Lapsus$, of course, is the possibly extinct extortion gang led by teenagers who went on a cybercrime spree last year before the arrest of its alleged ringleaders. Before that, however, it stole data from Nvidia, Samsung, Okta, and others.

It could be that Medusa is spreading around stuff that was already stolen and leaked.

[…]

Source: Medusa ransomware crew boasts of Microsoft code leak • The Register

Why Video Editors are Switching to DaVinci Resolve in Droves

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Video editors are flocking to DaVinci Resolve in droves, marking a major paradigm shift in the editing landscape that we haven’t seen since the dreadful launch of Final Cut Pro X drove users to Adobe Premiere Pro.

[…]

More a conglomeration of tools than a single program, Resolve came through some acquisitions Blackmagic made when creating a broadcast and cine ecosystem.

Comprised of an editing tool, a color correction tool, an audio editor, and an effects tool, Resolve is essentially multiple programs that all integrate so seamlessly that they function as a single application.

The color correction tools in Resolve are particularly well regarded, and many films and shows were color graded in Resolve even if they were edited in another program. The same applies to Fairlight, the audio component of Resolve, the go-tool tool for many of Hollywood’s most prominent audio engineers.

In 2011, Blackmagic decided to release Resolve as both a paid and a free version. The free version had fewer features than the full version (as it still does), but instead of being crippled, the free version works well enough for most users, with the paid version feeling like a feature upgrade.

[…]

There are a few key differences between the free and Studio version. Studio supports more video formats (and completes 4Kp60 workflows), uses the GPU more efficiently, has more effects, and fully supports the product’s audio, color, and effects tools.

It’s not the price alone that has caused a mass adoption of the program, though. It’s the company’s approach to updates as well.

Features

Blackmagic has never hesitated to put a feature into Resolve. The program has many options in contextual menus, user interface choices, menu items, keyboard shortcuts, and more.

There is so much here that it can be overwhelming. Finding the tool I want in a contextual menu is often the most challenging part of my editing. But if there’s something that can be done in video editing, a button, icon, or menu will probably perform the task.

Blackmagic also releases dot-versions (like 18.1) that sometimes add enough features that it acts like a full number upgrade would if it were released by Adobe or Apple. Some of the features in Resolve 18.1, for example, unleashed the wave of recent switchers.

Two significant features are buried in a list of around 20 new features in that update. The first is AI-driven Magic Mask tools that make masking people or objects a matter of drawing a line. The other prominent feature is voice isolation, another AI-based feature that removes noises from dialog tracks.

Magic Mask alone is worth the price of admission. This tool makes it easy to color-correct significant portions of a shot without doing endless mask adjustments, and it also allows for instant alpha channel creation, allowing for items like text, graphics or even people to be superimposed on the same scene without needing a green screen.

In noisy environments, this tool performs amazingly. I’ve used it to eliminate leaf blowers and lawnmowers in the background of outdoor shoots, and I’ve seen it used to cancel out hair dryers and drill guns in sample videos on some channels.

[…]

The Speed Editor costs $295 and comes with a Resolve Studio license, making it worth the cost even if you barely use it.

The Blackmagic Speed Edit deck is an excellent piece of hardware, though many functions are out of my league. Buttons are arranged where a seasoned editor would. Cinematographers, especially those working on multi-cam shoots, will benefit from this editing.

Or at least that’s why my seasoned editor friend tells me. The unit feels odd in my hands because I don’t use most of the keys. One central portion of the Speed Editor is dedicated to switching between up to nine cameras, but the device has encouraged me to do more multi-cam shoots since the keyboard makes editing smooth.

The keyboard, which connects via USB-C cable or Bluetooth, is labeled with the essential editing functions, which is very helpful for new Resolve users. Instead of memorizing the location of essential keys on a standard keyboard, new users can look at the Speed Editor and focus on learning editing workflow instead of shortcuts.

On the other hand, many seasoned editors already know all the keyboard shortcuts on a standard keyboard and have made their custom keyboard configurations to support their editing style. Even though I’m a new Resolve editor, many tasks are performed the same as Final Cut, so I moved toward the regular keyboard shortcuts.

The Speed Editor is an excellent example of the complete Blackmagic ecosystem, which is why the free program and Studio are low-cost.

[…]

: Just after finishing this article, Blackmagic announced a new version of Resolve, which adds several compelling features including transcriptions, subtitles, and the ability to edit clips by selecting text.

[…]

Source: Why Video Editors are Switching to DaVinci Resolve in Droves | PetaPixel

Scientists Identify Mind-Body Nexus In Human Brain

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An anonymous reader quotes a report from Reuters: Researchers said on Wednesday they have discovered that parts of the brain region called the motor cortex that govern body movement are connected with a network involved in thinking, planning, mental arousal, pain, and control of internal organs, as well as functions such as blood pressure and heart rate. They identified a previously unknown system within the motor cortex manifested in multiple nodes that are located in between areas of the brain already known to be responsible for movement of specific body parts — hands, feet and face — and are engaged when many different body movements are performed together.

The researchers called this system the somato-cognitive action network, or SCAN, and documented its connections to brain regions known to help set goals and plan actions. This network also was found to correspond with brain regions that, as shown in studies involving monkeys, are connected to internal organs including the stomach and adrenal glands, allowing these organs to change activity levels in anticipation of performing a certain action. That may explain physical responses like sweating or increased heart rate caused by merely pondering a difficult future task, they said. “Basically, we now have shown that the human motor system is not unitary. Instead, we believe there are two separate systems that control movement,” said radiology professor Evan Gordon of the Washington University School of Medicine in St. Louis, lead author of the study.

“One is for isolated movement of your hands, feet and face. This system is important, for example, for writing or speaking -movements that need to involve only the one body part. A second system, the SCAN, is more important for integrated, whole body movements, and is more connected to high-level planning regions of your brain,” Gordon said.

“Modern neuroscience does not include any kind of mind-body dualism. It’s not compatible with being a serious neuroscientist nowadays. I’m not a philosopher, but one succinct statement I like is saying, ‘The mind is what the brain does.’ The sum of the bio-computational functions of the brain makes up ‘the mind,'” said study senior author Nico Dosenbach, a neurology professor at Washington University School of Medicine. “Since this system, the SCAN, seems to integrate abstract plans-thoughts-motivations with actual movements and physiology, it provides additional neuroanatomical explanation for why ‘the body’ and ‘the mind’ aren’t separate or separable.”

The findings have been published in the journal Nature.

Source: Scientists Identify Mind-Body Nexus In Human Brain – Slashdot