NIST’s National Cybersecurity Center of Excellence (NCCoE) has teamed up with 15 large financial and state institutions, as well as tech companies, to research and develop a way of integrating Mobile Driver’s License (mDL) into financial services. But according to NIST, this is just the start and the initial focus of the program.

The agreement represents an effort to tie in yet more areas of people’s lives in their digital ID (“customer identification program requirements” is how NIST’s announcement describes the focus of this particular initiative). These schemes are often criticized by rights advocates for their potential to be used as mass surveillance tools.

As Visual Capitalist’s Dorothy Neufeld details below, from AI-driven advancements in disease detection to carbon-capturing microbes, these technologies stand to improve future society. Meanwhile, greater efficiencies in wireless connectivity allow networks to drive higher data rates and enhance robust communications across 6G networks and the industrial internet-of-things.

The above graphic shows the top 10 emerging technologies for 2024, based on data from the World Economic Forum.

Methodology

Technologies were selected from a survey based on 300 nominations across 29 countries, according to the below criteria:

• Power: The technology could critically transform industries and established behaviors
• Applicability: The technology has the potential for widespread use and benefit to economies
• Novelty: It is in the early stages of development, but yet to be widely used
• Depth: More than one country is developing and investing in the technology

Along with this criteria, technologies were selected based on their potential to make a significant impact on society over the next three to five years.

Leading Emerging Technologies of 2024

Below, we show the most promising emerging technologies of 2024:

Overall, AI-related technologies were driving two of the top 10 technologies across healthcare and data privacy industries.

Although AI for scientific discovery has been developing for some time, the current rate of innovation could accelerate the diagnoses and the treatment of diseases using language modelling. Along with this, deep learning, a subset of AI, can be used to further scientific discoveries.

In the realm of privacy-enhancing technologies, the use of “synthetic data” could play an important role in protecting sensitive data across large datasets. This involves using data that replicates the original data but does not include specific details that may be connected to people.

As a warming planet and extreme weather events increasingly disrupt global society, four of the top 10 technologies were focused on sustainable solutions. One compelling technology is carbon-capturing microbes, which are engineered through synthetic biology to absorb greenhouse gases. Not only that, these organisms can convert CO₂ into fertilizers and fuels through using sunlight to transform gases.

In addition, elastocalorics are a technology that increase the energy efficiency of heating and cooling systems. This is done through elastocaloric material getting hotter or cooler under exposure to mechanical stress. Importantly, this technology doesn’t rely on potentially environmentally harmful refrigerant gases, as global demand for space cooling is projected to triple in the next three decades.

As a result of the retraction, the number of effective electrodes was reduced, which in turn limited Arbaugh’s ability to control a computer cursor with his brain. In response, Neuralink modified the recording algorithm to be more sensitive to neural population signals, improved the techniques to translate these signals into cursor movements, and enhanced the user interface.

Following these adjustments, Neuralink reported a “rapid and sustained improvement” in the bits-per-second measure of speed and accuracy of cursor control, surpassing Arbaugh’s initial performance. The company has assured that the issue does not pose a safety risk to Arbaugh.

However, Neuralink reportedly considered removing his implant, according to The Wall Street Journal. The company has also informed the Food and Drug Administration that it believes it has a solution for the issue that occurred with Arbaugh’s implant.

Despite the setback, Neuralink highlighted Arbaugh’s achievements since receiving the implant just over 100 days ago, including his ability to play online computer games, browse the internet, livestream, and use other applications “all by controlling a cursor with his mind.”

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Article generated from corporate media reports.

Speaking at the Hill & Valley Forum’s gathering of top technology and government officials in Washington this week, Mulchandani’s made it clear that the agency is aggressively pursuing advancements in artificial intelligence (AI) to bolster both offensive and defensive capabilities, the Washington Times reports.

“We’re looking at transforming every single part of what the agency does,” he stated, underscoring the depth of the CIA’s commitment to integrating AI into its core operations. The agency’s push includes the development of large language models, sophisticated algorithms that are the backbone of generative AI tools, aiming to enhance everything from field operations to analytical and support functions.

This strategic pivot comes as geopolitical rivalry with China is intensifying. The CCP has repeatedly expressed its ambition to dominate the AI sphere, which would present profound challenges and implications for global power dynamics. Mulchandani emphasized the need to rethink the concept of this competition as a “race,” suggesting that viewing it as having a definitive end is a misstep. “This is an infinite race. This is not going to stop. It’s going to keep on going,” he explained, framing the scenario as a continuous struggle for technological superiority.

The implications of this shift are profound. If the deployment of these new tools escalates to warfare, it will test America’s position in the technology stakes, a scenario Mulchandani hopes will never materialize. He predicts the next major conflict will be “primarily a software war,” driven by AI, changing the nature of warfare from hardware-dependent to software-driven.

The concerns are not just theoretical. At Stanford’s Hoover Institution, Herbert Lin of the Stanford Emerging Technology Review highlighted the shift in global tech leadership, with the U.S. losing its primacy in certain key areas like AI. Lin pointed out the critical need for a robust talent pipeline and a strategic vision, especially in fields like biotechnology, to maintain competitiveness.

Moreover, the CIA is particularly wary of AI-driven Ubiquitous Technical Surveillance (UTS), which threatens the secrecy of U.S. intelligence operations. In response, the agency is engaged in foundational infrastructure work, which Mulchandani described as the “sewer and plumbing work” necessary to navigate the AI revolution. This involves constant adaptation to rapid technological changes, ensuring that the CIA remains agile in its tech tactics.

“We talk about UTS, which is basically something that’s really, really killing us out in the field in terms of competitively, you know, biometrics, video cameras,” he said. “Well, how do we turn it around [and continue] those operations in the face of this much AI being thrown at us is another big area that they’re looking at. So directorate by directorate, we’re rethinking, reshaping every part of what CIA needs to do in the face of using it and deploying it.”

The urgency of these initiatives is echoed in the broader governmental plea for collaboration from Silicon Valley. House Speaker Mike Johnson’s call to technologists and venture capitalists at the forum to guide and assist the government underscores the critical role of public-private partnerships in navigating the technological labyrinth.

As the U.S. and China continue their relentless pursuit of technological dominance, the narrative is clear: this is not a sprint with a finish line but a marathon without end, defining the future of global power, security, and technological innovation.

Big Mike Begs

No, not that Big Mike… House Speaker Mike Johnson (R?-LA), who implored the technologists and venture capitalists at the forum to help the government wherever they can.

“There are not many industries, not many leaders and experts, who we just openly plead for your counsel, but I am doing that here today,” said Johnson. “Because a lot of the people who are of goodwill here, who want to do the right thing, could use some of your guidance along the way to make sure that we don’t step on any land mines that we don’t see. You have a much better vision, I think, on a lot of that than we do.”

The U.S. Department of Transportation is investigating Tesla’s December 2023 recall, which pulled more than 2 million vehicles from the road, to determine whether the company’s updates to its Autopilot driving systems were sufficient in preventing driver distractions. The department analyzed 956 crashes that were alleged to involve the automaker’s driver assistance technology.

The department’s National Highway Traffic Safety Administration on April 26 posted documents to its website that suggest an additional 20 crashes occurred since Tesla’s recall, concerning investigators. The more than 2 million vehicles that Tesla recalled represent nearly all the vehicles that Tesla had sold at that point.

Tesla’s December 2023 recall affected all of its vehicles with Autopilot or driver assistance systems. This includes Tesla’s Model 3, Model X, Model S, and Model Y cars, as well as its Cybertruck. The Autopilot’s driver monitoring systems are supposed to detect the force from drivers’ hands on the steering wheel and send alerts when they are absent.

The safety administration asked the automaker to recall its vehicles after a two-year investigation into Tesla’s Autopilot system. Specifically, the agency probed multiple instances of Teslas crashing into roadside emergency vehicles while using the Autopilot systems.

The automaker said the “prominence and scope of the system’s controls may be insufficient to prevent driver misuse.”

The National Highway Traffic Safety Administration on April 26 said its two-year investigation into Tesla’s Autopilot system was done to find any problems with the technology that “created an unreasonable risk” to driver and vehicle safety, and “involved extensive crash analysis, vehicle evaluations, and assessment of vehicle control authority and driver engagement technologies.”

The administration’s Office of Detects Investigation found 13 crashes that involved one or more fatalities and several others that caused serious injuries in which “foreseeable driver misuse” of the Autopilot system played a key role.

For owners of vehicles that use driver assistance technology, Tesla sent an online software update to increase driver warnings, including when a driver’s hands leave the steering wheel. The agency found 20 additional crashes after Tesla sent the update.

Tesla also stated that the solution requires the driver to opt in but allows the driver to reverse the fail-safe, according to the agency.

Autopilot Allegedly Kills Motorcyclist

A 2022 Tesla Model S using the Autopilot driving system was allegedly linked to a motorcyclist’s death in Seattle, Washington, on April 19.

The vehicle owner told a Washington State Patrol trooper after the crash that he was using the driver assistance technology while looking at his phone and driving the car.

“The next thing he knew there was a bang and the vehicle lurched forward as it accelerated and collided with the motorcycle in front of him,” the police officer wrote in the affidavit.

The trooper arrested the 56-year-old driver for investigation of vehicular homicide after the driver said he was using the Autopilot mode while operating the car inattentively and using his cell phone as it moved forward, “putting trust in the machine to drive for him,” according to the document.

Authorities found the motorcyclist, Jeffrey Nissen, 28, underneath the car, and he was pronounced dead at the scene.

However, authorities are still investigating the crash and have not verified whether the driver was using Autopilot at the time of the incident.

The federal agency probing Tesla said it was looking for defects in Autopilot’s driver monitoring system, which is supposed to alert drivers when their hands are no longer touching the steering wheel. Some experts have alleged that the monitoring system is defective and have also criticized its limitations during night driving.

Teslas have cameras to monitor drivers on the road, but they do not possess night vision capabilities, and Autopilot is still operable when the cameras are covered.

The initial investigation began in 2021 after 11 reports surfaced of Teslas striking parked emergency vehicles while using Autopilot. Between June 8, 2022, and April 25, the Autopilot system caused 467 crashes and 14 fatalities.

Tesla said that both of its driver assistance systems—Autopilot and the advanced “Full Self Driving”—cannot drive themselves, despite the choice of the name.

The latter technology was linked to 75 crashes and one death, according to the investigation.

Tesla’s CEO Elon Musk previously promised a fleet of robotaxis driven with “Full Self Driving” to create revenue for both the company and the vehicles’ owners, as they can operate as taxis when they’d normally be parked. The cars are still being tested and have faced years of delays after Mr. Musk said they would be ready by 2020.

The company says drivers must always be ready to take control of the wheel when using Autopilot or “Full Self Driving” and that they do not give the vehicle complete autonomous control.

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The Epoch Times has reached out to Tesla for comment. The Associated Press contributed to this report.

(DCNF)—American technology company Nvidia has shot up in value over the last several years following speculation about the potential economic impact of new computing technology that some investors believe could increase productivity substantially.

Nvidia posted huge year-end quarterly profits Tuesday evening, up 265% from a year prior as the company continues to grow at breakneck speeds, according to the company’s fourth quarter results. The fourth quarter gain beat expectations and led to a $277 billion stock rally on Wednesday, up 16.3% in just the day, making it the largest single-day increase in the New York Stock Exchange’s history, according to Reuters.

Investor hype around Nvidia is due to its stake in the semiconductor market, where it commands a vast majority of market share in artificial intelligence (AI) related technologies, experts told the Daily Caller News Foundation. Many investors predict that AI and greater computing efficiency will be a boon to businesses, which could greatly increase productivity using the technology for a wide array of applications.

“Nvidia has already made strides in increased efficiency, which is a tremendous advantage in this regard due to the sheer volume of calculations that must be performed to make a technology like AI possible,” E.J. Antoni, a research fellow at the Heritage Foundation’s Grover M. Hermann Center for the Federal Budget, told the DCNF. “With the ability to position data centers virtually anywhere, size is not really a major issue anymore for chips, but efficiency is due to increased energy prices and environmental regulations. Being on the cutting edge of chip technology puts a firm in a position to truly command the market.”

Nvidia was first founded in 1993, introducing products related to 3D graphics, particularly for gaming and multimedia creation, and later invented the graphics processing unit in 1999, taking a big step for computing power, according to the company’s website. The company also claims to have sparked the era of modern AI in 2012, way ahead of trends around the technology, giving it a commanding lead on other technology companies that are now looking to catch up and expand into AI.

“Nvidia controls most (about four-fifths) of the chip market for AI-related technologies,” Antoni told the DCNF. “The explosion of demand around AI has boosted chip demand too, leading to growth forecasts for Nvidia that were completely off the table just a couple years ago. Like all stock prices, no one can say for sure if Nvidia’s current popularity is warranted because stock prices are speculation on future earnings, and the future is by definition uncertain. This is particularly true for AI, where so much of the potential is unknown.”

Nvidia’s stock price has exploded over the past few years, measuring less than $40 a share at the start of 2019, peaking at over $310 a share in November 2021, before sliding to around $127 a share in October 2022, ultimately climbing all the way to around $800 a share in February 2024, according to MarketWatch.

Nvidia breaks stock market record with a $247 billion one-day market cap surge, as reported by Bloomberg.

Renowned for AI & fast computing, #Nvidia hits a major financial milestone with its staggering revenue.

Stock up nearly 280% in the past year!#AI #Crypto #Stocks pic.twitter.com/Qv9aQ3LP14

— Christiaan (@ChristiaanDefi) February 23, 2024

“The fact that the demand for these products is growing indicates to me that our society, these companies, educational organizations, all the different users of AI believe that there is great value here that can improve our lives,” David Inserra, a fellow for free expression and technology at the Cato Institute, told the DCNF. “I can’t predict that it will certainly be that way. But every indicator that we have indicates that the market is saying there’s great value here. I think that we’d be foolish to ignore that important market indicator.”

Generative AI powered by the type of technology Nvidia is leading the way on is already finding several applications in business despite being in its infancy, including in customer service, cybersecurity, personal assistants, inventory management, accounting and more, according to Forbes. The U.S. is also looking to use semiconductor technology and AI in military applications and is trying to prevent China’s access to the equipment to maintain a technological and militaristic edge.

American companies controlled around 48% of the market share in the semiconductor market in 2022, compared to 7% in China, according to Statista. South Korea controlled the second-largest market share with 19%, followed by Japan and the European Union at 9%.

The Biden administration has placed a number of restrictions on the semiconductor industry to ensure continued American supremacy, including putting sanctions on several Chinese chip manufacturers in October 2022 to prevent them from working with American firms. Congress has also approved $39 billion in direct funding for chip manufacturers as part of the August 2022 Chip and Science Act.

The rollout of the funds has so far failed to bring a substantial number of chip manufacturing plants into operation, with several companies pushing back new plant completion dates to 2025 or later due to volatility in chip prices and government funding uncertainty.

The growth of generative AI powered by new chips has also led to concerns that the technology is being given a liberal skew, such as Google’s AI chatbot Gemini taking a nuanced position on the terrorist organization Hamas’ stance on the violent eradication of Israel and whether China is committing genocide against the Uyghur people.

Nvidia is part of what has been dubbed the Magnificent Seven Stocks, which are stocks that have delivered a large portion of stock growth in the past few years, according to Yahoo Finance. Tesla, an electric vehicle (EV) company, has had a similar meteoric rise starting slightly earlier but has since remained relatively stagnant in 2024 as other competitors in the EV field emerge, raising concerns that Nvidia might not live up to expectations.

“This is always the market dynamic, right? If someone comes along and delivers a more desirable product, well then yeah, sure,” Inserra told the DCNF about the potential for Nvidia to lose its current investor hype. “Right now we’re talking a lot about AI, but what if a new kind of AI, a better type or even more advanced, better type of technology emerges and uses different kinds of computing power? We don’t know what the future of innovation could bring. So to that extent, yeah, it’s possible that Nvidia isn’t going to be the golden child of this forever, but from what I’ve read, it seems like they have been forward-leaning and looking for ways to move into new spaces in the use of their processors for AI, and so right now they have that leg up.”

Nvidia declined to comment to the DCNF.

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“‘Biocomputer’ combines lab-grown brain tissue with electronic hardware”

“A system that integrates brain cells into a hybrid machine can recognize voices”

“Brainoware: Pioneering AI and Brain Organoid Fusion”

Scientists are trying to inject human brain tissue into artificial networks because AI isn’t working quite as well as we have been led to think. AI uses a horrendous amount of energy do its kind of parallel processing, while the human brain uses about a light bulb’s worth of power to perform similar feats. So, AI designers are looking to cannibalize some parts from humans to make artificial networks work as efficiently as human brains. But let’s put the fact of AI’s shortcomings aside for the moment and examine this new cyborg innovation.

The breakthrough in biocomputing reported by Hongwei Cai et al. in Nature Electronics involves the creation of a brain organoid. That is a ball of artificially-cultured stem cells that have been coaxed into developing into neurons.

The cells are not taken from someone’s brain—which relieves us of certain ethical concerns. But because this lump of neurons does not have any blood vessels, as normal brain tissue does, the organoid cannot survive for long. And so ultimately, the prospect of training organoids on datasets does not seem practical, economically speaking, at present.

But that is not going to stop this research.  The drive to seamlessly integrate biology and technology is strong.  But can it be done?  And why do so many research scientists and funding agencies assume it’s possible?

TRANSHUMAN HOPES

Underlying the hopes of a transhumanist is a philosophy of materialism that follows a logic something like this: living systems are composed of matter and energy: the interactions of all matter and energy can be represented in code, and the material used to create biohardware should be irrelevant and can be synthetic.

With such founding assumptions, transhumanists are confident they can learn to upgrade biological “hardware” with non-biological materials, and reprogram biological “software,” after cracking its “code,” and mix and match with electronics to augment human capabilities.

When researchers integrate brain tissue into an artificial network setup, they treat it as if it were the hardware they’re used to working with. They see each neuron as being either on or off—firing or not—like an electronic switch, and they see the dendrites connecting to other neurons like wires.

They see stronger connections between neurons as being “weighted,” in a statistical sense, through differential repeated interactions.

Not incidentally, if such minded people were to exercise their influence in education, they would treat students like neural networks that can be programmed by rote memorization, and they would assume that they could better trigger the targeted response by simply applying rewards and punishments. This technique produces automatons, not critical thinkers. But that’s another essay.

ORGANOIDS MIGHT HAVE A DIFFERENT KIND OF INTELLIGENCE

If researchers think of living systems as digitized computers, they are going to have trouble with their organoids. What if neurons process information very differently from the way that artificial neural nets do?  What if neurons communicate with each other by propagating bioelectric waves through a medium? and what if, when they fire, it’s like rain drops creating concentric rings in a pool of water, with the clashing concentric rings creating interference patterns? What if it’s complicated?

Researchers in my field, Biosemiotics, are now asking such questions.  And in their vision of brain activity, neurons are not just connected as if with wires, but are coordinated with each other by virtue of their shared milieu. When a human brain has a thought, three dimensional bioelectric waves wash over the tissue, creating virtual connections — groups affected by the wave become momentarily coordinated. I don’t think there is an analogous process going on in an artificial neural network, where fluidity is only a metaphor and the structure of the setup is a lot more brittle and fixed.

An incredibly complex system like an organoid cannot be understood better by thinking of it in terms of a less complex system like a circuit board. Each neuron has the benefit of billions of years of evolution; environmental conditions can trigger DNA to produce a variety of proteins for all sorts of uses. Each cell has complex little organelles (that are descended from free-roaming protist creatures!) to handle the processing of all sorts of different signals from the outside. Each cell has receptors and little ion-gated pores that filter signals.

But I’m not a bio snob. Computers are incredible tools in the hands of people.  But can/should digital computers be tools inside the heads of people or can/should brain tissue be incorporated into digital computers?

BRAINOWARE: HOW IT WORKS

The setup for the invention described in the Nature Electronics article is remarkably simple. The organoid is placed on 2D high-density multielectrode array (MEA), which emits electric pulses, to which the organoid neurons respond by producing their own electrical patterns. This device has been dubbed, “Brainoware,” and it can recognize voices.

First, voice recordings are made and digitized into a 2D pattern that can be modeled on the 2D MEA. This digitized voice model is the input used to stimulate the brain organoid, which, in turn, outputs a pattern that reflects both the voice model and the internal structure of the organoid’s own dynamics. The neurons stimulate and are stimulated by other neurons in a non-linear fashion, that is, some features maybe be dampened, others amplified.

The above illustration of the setup is from the actual article, not from a pre-school reader version of the article.

The experiment was declared a success when, after training, the organoid had improved its ability to distinguish the vowel sounds of a male speaker from seven other male and female speakers. Prior to training, the setup could distinguish the speaker about 51% of the time, and after training, it was about 78% accurate.

BUT WAIT!

Before we get too excited about this success of finally merging man and machine, using enslaved brain cells to build a computer that can eavesdrop on our conversations, I note that over twenty years ago, a very similar experiment was done with a perturbed bucket of water performing a similar role as the brain organoid.

In that experiment, the water was used to distinguish between voice recordings of the words, “One” and “Zero,” with an error rate of only 1.5%. Below is a picture of these researchers’ three–dimensional models of the spoken words.

It is my opinion that the Brainoware researchers are not using the full potential of a neuron, if a bucket of water can “process” information better than a brain organoid. It’s a bit like using Shakespeare’s collected works as a doorstop.

In “Pattern Recognition in a Bucket,” Chrisantha Fernando and Sampso Sojakka note that similar experiments on have been done at the Unconventional Computing Laboratory, run by the devilishly charming Andy Adamatzky at the University of the West of England, Bristol UK. For many years now, Adamatsky has used chemicals (forming reaction-diffusion waves) and slime mold to do computation and act as memory reservoirs.

WHAT IS A COMPUTER RESERVOIR?

I had to look this up.  Reading computer science papers is—for me, a philosopher of science who originally started out in literary theory—reminiscent of reading Jacqueses Lacan and Derrida; there is a lot of unnecessarily opaque terminology covering up rather mundane statements.

I gather that a reservoir can be any kind of physical system that is made of individual units that can interact with each other in non-linear ways, and these units must be capable of being changed by the interaction. Even a bucket of water can function as a reservoir, apparently. Miguel Soriano explains it this way in “Viewpoint: Reservoir Computing Speeds Up,”

Reservoirs are able to store information by connecting the units in recurrent loops, where the previous input affects the next response. The change in reaction due to the past allows the computers to be trained to complete specific tasks.

Hope that helps.

Reservoirs are also referred to as “black boxes” because the researchers don’t know (or don’t have to know) the complex dynamics that go on while transforming the input into the output. I reckon that, because every spoken word is never quite the same twice, a non-linear system must process that sound so that it captures an essence of what it is and can identify the same word again and again in very different contexts.

Computer Redesign?

Science Fiction is often ahead of actual research.  In the movie Ex Machina, the femme fatale robot has an artificial brain that is made out of gel, not silicon chips and electronic switches. She might have come out of Adamatsky’s unconventional computing lab.

One of my colleagues, J. Augustus Bacigalupi, proposed a computer redesign called Synthetic Cognition back in 2012, based on an understanding that biological information processing looks a bit more like this:

than this:

Bacigalupi envisioned a terrain emerging in the medium between neurons and imagined that the intersections of diffusing signals, the interference, could itself be harnessed as a useful signal. He suggests that such a different approach would make computers much more efficient insofar as they would naturally integrate multiple signals for free.

Since that early hardly-watched lecture on Synthetic Cognition (while TED talks by Nicholas Negroponte of MIT Media Lab—who thinks we will soon be able to ingest digitized Shakespeare as a pill—get a lot more views), Bacigalupi has gone on to specialize in Biosemiotics, writing papers with me and our mutual colleague, Don Favareau, like their latest one in the Journal of Physiology.

A dozen years ago Bacigalupi saw cyborgs in our future if we used his proposed new technology that would be able to harness what’s special about brain organoids and slime mold.

But the integration of man and machine faces banal challenges, like rotting organic matter and inflammation of cells in contact with the various chemicals of electronic devices.

There is a reason why most of Elon Musk’s Neuralinked primates didn’t make it. A similar issue here is the unintended (we hope!) side-effects of synthetic pharmacological interventions, which are the bane of that industry. You see, biological cells tend to make interpretations of signs, not strict decryptions of code. Such flexibility allows adaptive creativity to happen, as well as terrible, unpredictable outcomes, for example, various autoimmune diseases.

Even relatively simple transhuman tech, like pacemakers and hip replacements can, in some people, provoke allergic reactions to metals.

And I don’t see the point of cannibalizing biology so that computer scientists can make robots pass the Turing Test better.  I do see, for example, NASA’s Artemis team using redesigned technology to create better robots, whose proprioception avails itself of a fluid medium capable of generating interference patterns that help orient it while it explores the lunar surface. Imitating the way biological organisms process information to make better, more reliable and efficient tools, seems common sense.

But I don’t see the point of making tools seem human—or of mixing human and electronic parts.

COMPUTER SLAVES

As Ian McEwan makes clear in his 2019 novel, Machines Like Me, the point of making a humanoid robot is to use it as a sex toy and a dishwasher. The drive to dehumanize people into cyborgs or to humanize robots probably grows out of the fact that it is no longer considered okay to enslave ordinary humans (or spouses).

I suspect that those who want a humanoid computer want a perfect mate, who knows everything about the master, can anticipate his every thought and move, and responds accordingly.  Such perfection in a mate does not allow it to express its own opinions or come up with its own goals and purposes.

It is worth going beyond the hype of headlines to explore these issues further.  We can learn a lot about ourselves in doing so. I lead a monthly webinar called We Are not Machines through IPAK-EDU where my students and I explore these kinds of issues.

Despite some concerted efforts to terrorize us, I do not believe we are about to be replaced in the workforce (only the shit jobs will go) and I don’t believe computers will be capable any minute now of taking over and turning us into workerborgs or batteries.

You are amazing just as you are, with your wonky neurons and your viscous brain.  And if we perfect our external tools and use them wisely, we can be even better.

First unveiled back in 2020, Ballie’s latest hypothetical design is roughly the size of a bowling ball on wheels – previously it was only about the size of a tennis ball. The spying device also now contains a built-in projector that can display a virtual work call, a yoga program, or whatever else the user wants projected on a wall or ceiling – the video below shows what Ballie looks like and what it does:

4. AI Robot companion called 'Ballie' by Samsung pic.twitter.com/dPV9dn9hsl

— Rowan Cheung (@rowancheung) January 9, 2024

(Related: Previously, Amazon’s Echo device was considered to be the ultimate spy machine to listen to and record everything users do and say.)

Does the world really need another in-home spying device?

At the recent CES 2024 event, Samsung showed off the Ballie in a demo, though attendees were not allowed any one-on-one time with the spherical robot device. In the demo, Ballie’s movements were “obviously tightly scripted and controlled,” to quote Engadget‘s Nathan Ingraham.

Ingraham says the demo “at the very least … gave us an idea of how the company envisions Ballie being used.” In other words, Ballie’s real-life use cases are still all hypothetical as the device is still under development.

An actor at CES 2024 asked Ballie to start a workout routine for him, which prompted the machine to project a workout video on the wall for immediate use, along with music to go along with it.

“Sure, you could just use your TV for that, but when one of the exercises called for laying down, Ballie shot the video to the ceiling so the actor could continue following along,” Ingraham explains.

In another demo example, Ballie displayed a visual representation of the air quality of a home to which it was connected via an air purifier. Ballie displayed not only particulate statistics but also a warning that the filter in the air purifier needed changing.

“The idea here is to show that Ballie can talk to all your smart home devices and display info from them, even if they don’t have a dedicated display,” Ingraham says.

Much like a smartphone, Ballie is also able to display a user’s calendar, place phone calls and even show video footage of, say, the inside of one’s “smart” Samsung refrigerator or the front stoop in the pathway of a “smart” doorbell.

“It’s cute, and it was fun to see Ballie confidently rolling around the floor of the demo area, but I can’t help but think that it’s solving exactly zero real world problems either,” Ingraham further notes.

According to Samsung, the first working Ballie devices will be on sale towards the end of the year, but not everyone, including Ingraham, is convinced it will actually materialize.

“I’m not fully convinced, as we’ve seen a lot of similar projects die in the wind, but I am definitely rooting for the little robot,” he writes.

Reports indicate that the latest iteration of Ballie presented at CES 2024 contains a spatial LiDAR sensor and a 1080p projector, the latter of which has two lenses and allows the robot to project movies, video calls and “greetings” on its surrounding surfaces.

A video shown during the device’s keynote depicted Ballie greeting a user who just returned home from work or an errand by projecting the word “Welcome” on the wall.

The latest news about the tech industry’s spying efforts can be found at Watched.news.

Sources for this article include:

• Engadget.com
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• NaturalNews.com

The communist nation, which controls 90 percent of the refined rare earth metal market, completely banned the rare earth extraction and separation technology. According to freelance writer and communications consultant Kurt Cobb, this recent move is part of a broader trade war between the United States and China over the exchange of technology.

President Xi Jinping’s commerce ministry sought public opinion last December on the potential move to add the technology to prepare samarium-cobalt magnets, neodymium-iron-boron magnets and cerium magnets to its “Catalogue of Technologies Prohibited and Restricted from Export.” In the list it also banned technology to make rare-earth calcium oxyborate and production technology for rare earth metals, adding them to a previous ban on the production of rare earth alloy materials.

Beijing is said to produce 60 percent of the ore, which means that the whole world is sending three-quarters of its ore to the country for processing, putting it in a commanding position to decide “who will get these metals and even whether the rest of the world gets any at all,” the analyst said. When China unexpectedly and dramatically reduced its rare earth exports in 2010, prices went skyrocketing. For Cobb, the Chinese would want to monopolize the market and even though America has made efforts to incentivize domestic mining of critical minerals, challenges remain due to the East Asian country’s market dominance. President Joe Biden’s administration allocated a small amount of budget to roll out a modest program to incentivize U.S.-based mining of critical minerals such as lithium, nickel, graphite, cobalt and manganese. However, it seemed to have failed.

“A private attempt to revive a closed rare earth mine, the largest in the United States, resulted in a colossal financial loss for investors when rare earth prices plummeted after China resumed its previous level of exports following the reduction in 2010,” Cobb wrote on his blogsite entry dated Dec. 24. “This shows how China can easily sabotage any attempts to challenge its dominance of the rare earth market.”

He added that the only reasonable way to break the Chinese stranglehold on the rare earth market would be for governments to guarantee the price of rare earth mined by domestic companies as CCP and its rare earth industry have a close-tie relationship. “In a world where the consensus regarding the free exchange of goods is breaking down and geopolitical interests are coming to the fore, China seems to care far less about living up to free trade rules than protecting its perceived national interests,” he said. “If other major trading countries and blocks start moving in the same direction, the easy availability of cheap goods and resources produced in faraway locales may become increasingly problematic.”

First U.K. rare earths hub launched

On the other side of the planet, a rare earth hub set up by the University of Birmingham, HyProMag Ltd and Mkango in Tyseley, central England, has already begun producing recycled rare earth for the magnets, an initiative re-introducing commercial sintered magnet manufacturing back into the U.K. for the first time in over 20 years.

Partners of the firm explained via a press release that Tyseley Energy Park is employing a mechanism dubbed Hydrogen Processing of Magnet Scrap (HPMS), a short-loop recycling method delivering materials that need only a few process steps to produce recycled ‘sintered’ rare earth permanent magnets that are made to recognized industrial grades. The process claimed to offer 88 percent energy saving and 98 percent human toxicity saving when compared to primary production and is considered a “cleaner and more energy efficient process than the traditional dismantling, thermal demagnetization and cleaning processes and lends itself to automated and efficient processing.”

At present, this is reported to be the only local source of recycled rare earth permanent magnets in the United Kingdom and is set to provide further customer and project partner samples. Commercial production is targeted for 2024, with initial throughput targets of 20 tons per year of rare earth magnets and alloys, scaling up to a minimum of 100 tpa in subsequent months. (Related: Demand for “critical” rare-earth minerals soars amid rapid growth of “clean” energy industry.)

Analysts are closely watching if China would also find a way to hinder its operations as well.

Head over to CommunistChina.news for more stories similar to this.

Sources for this article include:

• OilPrice.com
• Money.USNews.com
• ResourceInsights.Blogspot.com
• Mining.com

The 68-year-old tech mogul shared his thoughts on the future of the workplace during an interview with comedian and writer Trevor Noah on his podcast “What Now.”

Billionaire philanthropist Mr. Gates said that while he does not believe advanced AI will replace humans entirely, its rapid expansion and adoption could change the labor market “forever,” potentially leading to a three-day workweek for humans.

“In the near term, the productivity gains you get from AI is very exciting,” he said. “It’s taking away part of the drudge work.”

Mr. Gates pointed to an example in which AI would likely be used in the near future, such as for medical professionals who are required to fill in paperwork.

In this case, AI could be used to “listen in” and help fill in the paperwork instead, effectively replacing the individual’s workload. Mr. Gates did not specify exactly what the AI software would “listen in” on.

The technology could also be used to tutor students or provide medical doctor “advice” for individuals in various parts of the world such as Africa, where access to health care is limited, he said.

Elaborating further on AI’s possible influence on the workforce, the billionaire said: “If you zoom out, the purpose of life is not just to do jobs. So, if you eventually get to a society where you only have to work three days a week or something, that’s probably OK. If the machines can make all the food and the stuff we don’t have to work as hard.”

Increased ‘Leisure’ Time

Mr. Gates went on to acknowledge that there would likely be “displacements” in the labor market owing to AI but said these would be “generalized” if they “come slow enough.”

“If it proceeds at a reasonable pace and the government helps those people who have to learn new things, then it’s all good,” he said.

“If you free up human labor, you can help elder people better, have smaller class sizes, you know, the demand for labor to do good things is still there,” he added. “And then if you ever get beyond that, you have a lot of leisure time and you’ll have to figure out what to do with it.”

Mr. Gates’s comments come after the makers of ChatGPT warned earlier this year that AI could “exceed expert skill level” across most domains within the next 10 years as “superintelligence” becomes more powerful than any “other technologies humanity has had to contend with.”

In a blog post published in May, OpenAI executives including CEO Sam Altman—who was recently reinstated to his job—co-founder Greg Brockman, and co-founder and chief scientist Ilya Sutskever, said it is highly “conceivable” that within the next 10 years, AI systems could carry out as much productivity as one of today’s largest corporations.

The World Economic Forum (WEF) has also warned that widespread use of AI could disrupt employment in the United States over the next five years, impacting roughly 23 percent of jobs by 2027.

According to WEF’s “The Future of Jobs Report 2023,” published in May, 69 million new jobs will likely be created through increased use of AI, while 83 million could be eliminated, resulting in a decrease of 14 million jobs, or 2 percent of current employment.

The WEF found that clerical or secretarial roles, including bank tellers, cashiers and ticket clerks, data entry clerks, postal service clerks, and administrative and executive secretaries will likely see the fastest decline in roles over the next five years relative to their size today.

Amazon to Train Millions on AI

Meanwhile, certain tech jobs, including those focused on AI and machine learning, would likely see a rise in employment.

Other experts, including Goldman Sachs economists, have forecast that two-thirds of occupations across the United States could be partially automated by AI.

More recently, JPMorgan’s CEO Jamie Dimon told Bloomberg that the next generation of workers will likely only need to go to the office 3.5 days a week thanks to AI.

“Your children are going to live to 100 and not have cancer because of technology,” Mr. Dimon told the publication. “And literally they’ll probably be working three-and-a-half days a week.”

Multiple companies in the United States and abroad have taken part in pilot programs testing four-day work weeks in recent years, during which employees still receive 100 percent of their wages.

Advocates argue the reduction in office hours will improve business productivity, worker health, and well-being, boost recruitment, retain employees, and reduce the carbon footprint of firms by reducing both commuting and energy use.

Mr. Gates’s comments came just after Amazon revealed plans to train and educate millions of people across the globe on AI amid a growing need for an AI-savvy workforce.

Amazon said it aims to provide training and education on AI skills—including how to make use of the generative AI technology behind language-based models such as ChatGPT—free of charge to 2 million people worldwide by 2025.