#computers/consumer electronics

[salmonella-destroyer-of-worlds]

[kekwcomics]

"Not all optical disks are the same"

MAC USER magazine (1991)

[asfe-joe]

Pictured: a very spicy pillow pulled from a laptop at work.

For those unaware: these batteries, usually pulled from laptops, but also found in phones, (looking at you note 7) are normally flat, but as they age, they can become "spicy", and if damaged/punctured, can burst into flames and/or explode

[reportwire]

Tesla, Apple, Ciena, and More Stock Market Movers

This copy is for your personal, non-commercial use only. To order presentation-ready copies for distribution to your colleagues, clients or customers visit http://www.djreprints.com. https://www.barrons.com/articles/stock-market-movers-6acba64b Updated March 6, 2023 5:37 am ET / Original March 6, 2023 5:07 am ET Order Reprints Print Article Stock futures traded mostly flat Monday as Wall…

[coupleofdays]

Adding another wrinkle to the "on what date did Tron actually take place?" confusion: When Dillinger talks to the MCP at the beginning on the film, there's the following exchange:

MCP: "Hello, Mr. Dillinger. Thanks for coming back early."

Dillinger: "No problem, Master C. If you've seen one consumer electronic show, you've seen them all. What's up?"

The Consumer Electronics Show, or CES for short, has been running annually at different venues since 1967. If we assume that Tron is set in the year 1982, then the CES of that year was held in Chicago on June 3-6 (it was where the Commodore 64 was shown for the first time!). So if it's this particular "consumer electronic show" Dillinger is referring to, presumably the film would take place in early June?

(Of course, it would be easy to simply say that in the movie universe, CES was held at a different date that year.)

(CES 1982 photos by Alan Light)

[jcmarchi]

Elaine Liu: Charging ahead

New Post has been published on https://thedigitalinsider.com/elaine-liu-charging-ahead/

Elaine Liu: Charging ahead

MIT senior Elaine Siyu Liu doesn’t own an electric car, or any car. But she sees the impact of electric vehicles (EVs) and renewables on the grid as two pieces of an energy puzzle she wants to solve.

The U.S. Department of Energy reports that the number of public and private EV charging ports nearly doubled in the past three years, and many more are in the works. Users expect to plug in at their convenience, charge up, and drive away. But what if the grid can’t handle it?

Electricity demand, long stagnant in the United States, has spiked due to EVs, data centers that drive artificial intelligence, and industry. Grid planners forecast an increase of 2.6 percent to 4.7 percent in electricity demand over the next five years, according to data reported to federal regulators. Everyone from EV charging-station operators to utility-system operators needs help navigating a system in flux.

That’s where Liu’s work comes in.

Liu, who is studying mathematics and electrical engineering and computer science (EECS), is interested in distribution — how to get electricity from a centralized location to consumers. “I see power systems as a good venue for theoretical research as an application tool,” she says. “I’m interested in it because I’m familiar with the optimization and probability techniques used to map this level of problem.”

Liu grew up in Beijing, then after middle school moved with her parents to Canada and enrolled in a prep school in Oakville, Ontario, 30 miles outside Toronto.

Liu stumbled upon an opportunity to take part in a regional math competition and eventually started a math club, but at the time, the school’s culture surrounding math surprised her. Being exposed to what seemed to be some students’ aversion to math, she says, “I don’t think my feelings about math changed. I think my feelings about how people feel about math changed.”

Liu brought her passion for math to MIT. The summer after her sophomore year, she took on the first of the two Undergraduate Research Opportunity Program projects she completed with electric power system expert Marija Ilić, a joint adjunct professor in EECS and a senior research scientist at the MIT Laboratory for Information and Decision Systems.

Predicting the grid

Since 2022, with the help of funding from the MIT Energy Initiative (MITEI), Liu has been working with Ilić on identifying ways in which the grid is challenged.

One factor is the addition of renewables to the energy pipeline. A gap in wind or sun might cause a lag in power generation. If this lag occurs during peak demand, it could mean trouble for a grid already taxed by extreme weather and other unforeseen events.

If you think of the grid as a network of dozens of interconnected parts, once an element in the network fails — say, a tree downs a transmission line — the electricity that used to go through that line needs to be rerouted. This may overload other lines, creating what’s known as a cascade failure.

“This all happens really quickly and has very large downstream effects,” Liu says. “Millions of people will have instant blackouts.”

Even if the system can handle a single downed line, Liu notes that “the nuance is that there are now a lot of renewables, and renewables are less predictable. You can’t predict a gap in wind or sun. When such things happen, there’s suddenly not enough generation and too much demand. So the same kind of failure would happen, but on a larger and more uncontrollable scale.”

Renewables’ varying output has the added complication of causing voltage fluctuations. “We plug in our devices expecting a voltage of 110, but because of oscillations, you will never get exactly 110,” Liu says. “So even when you can deliver enough electricity, if you can’t deliver it at the specific voltage level that is required, that’s a problem.”

Liu and Ilić are building a model to predict how and when the grid might fail. Lacking access to privatized data, Liu runs her models with European industry data and test cases made available to universities. “I have a fake power grid that I run my experiments on,” she says. “You can take the same tool and run it on the real power grid.”

Liu’s model predicts cascade failures as they evolve. Supply from a wind generator, for example, might drop precipitously over the course of an hour. The model analyzes which substations and which households will be affected. “After we know we need to do something, this prediction tool can enable system operators to strategically intervene ahead of time,” Liu says.

Dictating price and power

Last year, Liu turned her attention to EVs, which provide a different kind of challenge than renewables.

In 2022, S&P Global reported that lawmakers argued that the U.S. Federal Energy Regulatory Commission’s (FERC) wholesale power rate structure was unfair for EV charging station operators.

In addition to operators paying by the kilowatt-hour, some also pay more for electricity during peak demand hours. Only a few EVs charging up during those hours could result in higher costs for the operator even if their overall energy use is low.

Anticipating how much power EVs will need is more complex than predicting energy needed for, say, heating and cooling. Unlike buildings, EVs move around, making it difficult to predict energy consumption at any given time. “If users don’t like the price at one charging station or how long the line is, they’ll go somewhere else,” Liu says. “Where to allocate EV chargers is a problem that a lot of people are dealing with right now.”

One approach would be for FERC to dictate to EV users when and where to charge and what price they’ll pay. To Liu, this isn’t an attractive option. “No one likes to be told what to do,” she says.

Liu is looking at optimizing a market-based solution that would be acceptable to top-level energy producers — wind and solar farms and nuclear plants — all the way down to the municipal aggregators that secure electricity at competitive rates and oversee distribution to the consumer.

Analyzing the location, movement, and behavior patterns of all the EVs driven daily in Boston and other major energy hubs, she notes, could help demand aggregators determine where to place EV chargers and how much to charge consumers, akin to Walmart deciding how much to mark up wholesale eggs in different markets.

Last year, Liu presented the work at MITEI’s annual research conference. This spring, Liu and Ilić are submitting a paper on the market optimization analysis to a journal of the Institute of Electrical and Electronics Engineers.

Liu has come to terms with her early introduction to attitudes toward STEM that struck her as markedly different from those in China. She says, “I think the (prep) school had a very strong ‘math is for nerds’ vibe, especially for girls. There was a ‘why are you giving yourself more work?’ kind of mentality. But over time, I just learned to disregard that.”

After graduation, Liu, the only undergraduate researcher in Ilić’s MIT Electric Energy Systems Group, plans to apply to fellowships and graduate programs in EECS, applied math, and operations research.

Based on her analysis, Liu says that the market could effectively determine the price and availability of charging stations. Offering incentives for EV owners to charge during the day instead of at night when demand is high could help avoid grid overload and prevent extra costs to operators. “People would still retain the ability to go to a different charging station if they chose to,” she says. “I’m arguing that this works.”

[uvaldecomputerrepairsstuff]

The Right to Repair: Why It Matters for You and Your Devices

In recent years, there’s been a growing movement advocating for the “Right to Repair.” But what does that actually mean, and why should you care? At its core, the Right to Repair is all about empowering consumers like you to have control over the devices you own—whether it’s your smartphone, laptop, or even your car. Let’s dive into what this movement is, why it matters, and how it affects you as…

[expopeak]

Hong Kong Electronics Fair – Autumn Edition 2024 https://expopeak.com/event/hong-kong-electronics-fair-autumn-edition-2024/

[infinities-and-binaries]

Philips in the 80s-90s was in the forefront of revolutionary tech, especially CDs.

_1987_Philips

[virtualrealitynewstoday]

Apple Vision Pro 將於2月2日在美國上市，空間計算時代來臨，預購將於1月19日開始

[nrmlcnsmr]

Snapdragon X Is Qualcomm's Answer To Apple's M2

Apple’s M2 chip is undoubtedly one of, if not the most powerful chip in a computer. However, the Snapdragon X from Qualcomm looks poised to challenge the M2 for supremacy (via Digital Trends) Snapdragon X Rebrand Snapdragon X will be a rebranding of Qualcomm’s current PC platforms and will roll out in 2024. It isn’t just a name change, though. The Snapdragon X chips will feature Qualcomm’s…

[bishtmeenakshi]

The Future of Consumer Electronics: Market Insights and Forecast

Stay ahead in the ever-evolving consumer electronics market. Explore the latest trends, growth opportunities, and innovative technologies shaping the industry. Be a part of the future of electronics.

[lindamarcis-blog]

Tech Odyssey 2023: Navigating the Seas of Innovation

Charting a Course Through the Technological Frontier:      Provide an engaging introduction that highlights the rapid pace of technological advancements. Mention the importance of staying updated with emerging technologies in today’s world. Section 1: AI and Machine Learning Revolution: Discuss recent developments in artificial intelligence and machine learning. Highlight real-world…

[reportwire]

Silicon Valley Confronts the End of Growth. It’s a New Era for Tech Stocks.

Silicon Valley could use a reboot. The biggest players aren’t growing, and more than a few are seeing sharp revenue declines. Regulators seem opposed to every proposed merger, while legislators push for new rules to crack down on the internet giants. The Justice Department just can’t stop filing antitrust suits against Google. The initial public offering market is closed. Venture-capital…

[faultfalha]

Nvidia has announced the availability of DGX Cloud on Oracle Cloud Infrastructure. DGX Cloud is a fast, easy and secure way to deploy deep learning and AI applications. It is the first fully integrated, end-to-end AI platform that provides everything you need to train and deploy your applications.

[jcmarchi]

Ubitium Secures $3.7M to Revolutionize Computing with Universal RISC-V Processor

New Post has been published on https://thedigitalinsider.com/ubitium-secures-3-7m-to-revolutionize-computing-with-universal-risc-v-processor/

Ubitium Secures $3.7M to Revolutionize Computing with Universal RISC-V Processor

Ubitium, a semiconductor startup, has unveiled a groundbreaking universal processor that promises to redefine how computing workloads are managed. This innovative chip consolidates processing capabilities into a single, efficient unit, eliminating the need for specialized processors such as CPUs, GPUs, DSPs, and FPGAs. By breaking away from traditional processing architectures, Ubitium is set to simplify computing, slash costs, and enable advanced AI at no additional expense.

The company has secured $3.7 million in seed funding to accelerate the development of this revolutionary technology. Investors Runa Capital, Inflection, and KBC Focus Fund are backing Ubitium’s vision to disrupt the $500 billion processor market and introduce a truly universal processor that makes computing accessible and efficient across industries.

Revolutionizing a $700 Billion Industry

The global semiconductor market, already valued at $574 billion in 2022, is projected to exceed $700 billion by 2025, fueled by increasing demand for AI, IoT, and edge computing solutions. However, traditional processing architectures have struggled to keep up with evolving demands, often relying on specialized chips that inflate costs and complicate system integration.

Ubitium addresses these challenges with its workload-agnostic universal processor, which uses the same transistors for multiple tasks, maximizing efficiency and minimizing waste. This approach not only reduces the size and cost of processors but also simplifies system architecture, making advanced AI capabilities viable even in cost-sensitive industries like consumer electronics and smart farming.

A RISC-V Revolution

The foundation of Ubitium’s processor is the open RISC-V instruction set architecture (ISA). Unlike proprietary ISAs, RISC-V fosters innovation by allowing companies to build on an open standard. Ubitium leverages this flexibility to ensure its processors are compatible with existing software ecosystems, removing one of the biggest barriers to adoption for new computing platforms.

Ubitium’s processors require no proprietary toolchains or specialized software, making them accessible to a wide range of developers. This not only accelerates development cycles but also reduces costs for businesses deploying AI and advanced computing solutions.

An Experienced Team Driving Change

Ubitium’s leadership team brings together decades of experience in semiconductor innovation and business strategy. CTO Martin Vorbach, who holds over 200 semiconductor patents, spent 15 years developing the technology behind Ubitium’s universal processor. His expertise in reconfigurable computing and workload-agnostic architectures has been instrumental in creating a processor that can adapt to any task without the need for multiple specialized cores.

CEO Hyun Shin Cho, an alumnus of the Karlsruhe Institute of Technology, has over 20 years of experience across industrial sectors. His strategic leadership has been key in assembling a world-class team and securing the necessary funding to bring this transformative technology to market.

Chairman Peter Weber, with a career spanning Intel, Texas Instruments, and Dialog Semiconductor, brings extensive industry expertise to guide Ubitium’s mission of democratizing high-performance computing.

Investor Confidence in Ubitium

The $3.7 million seed funding round reflects strong investor confidence in Ubitium’s disruptive potential. Dmitry Galperin, General Partner at Runa Capital, emphasized the adaptability of Ubitium’s processor, which can handle workloads ranging from simple control tasks to massive parallel data flow processing.

Rudi Severijns of KBC Focus Fund highlighted the reduced complexity and faster time-to-market enabled by Ubitium’s architecture, describing it as a game-changer for hardware and software integration. Jonatan Luther-Bergquist of Inflection called Ubitium’s approach a “contrarian bet” on generalized compute capacity in a landscape dominated by chip specialization.

Addressing Key Market Challenges

One of the major barriers to deploying advanced computing solutions is the high cost and complexity of specialized hardware. Ubitium’s universal processor removes this hurdle by offering a single-chip solution that is adaptable to any computing task. This is especially critical for industries where cost sensitivity and rapid deployment are paramount.

For example, in the automotive sector, where AI-powered systems like autonomous driving and advanced driver-assistance systems (ADAS) are becoming standard, Ubitium’s processors can streamline development and reduce costs. Similarly, in industrial automation and robotics, the universal processor simplifies system architectures, enabling faster deployment of intelligent machines.

Applications Across Industries

Ubitium’s universal processor is designed for scalability, making it suitable for a wide range of applications:

Consumer Electronics: Enables smarter, more cost-effective devices with enhanced AI capabilities.

IoT and Smart Farming: Provides real-time intelligence for connected devices, optimizing resource use and increasing efficiency.

Robotics and Industrial Automation: Simplifies the deployment of intelligent machines, reducing time-to-market for robotics solutions.

Space and Defense: Delivers high-performance computing in challenging environments where reliability and adaptability are critical.

Future Roadmap

Ubitium is not stopping with a single chip. The company plans to develop a portfolio of processors that vary in size and performance while sharing the same architecture and software stack. This approach allows customers to scale their applications without changing development processes, ensuring seamless integration across devices of all sizes.

The ultimate goal is to establish Ubitium’s universal processor as the standard platform for computing, breaking down the barriers of cost and complexity that have historically limited the adoption of AI and advanced computing technologies.

Transforming Human-Machine Interaction

Ubitium envisions a future where machines interact naturally with humans and each other, making intelligent decisions in real time. The flexibility of its processors enables the deployment of advanced AI algorithms, such as object detection, natural language processing, and generative AI, across industries.

This shift not only transforms the way we interact with technology but also democratizes access to high-performance computing, enabling innovation at all levels.