Archive for the ‘Artificial Intelligence’ Category

Lithography-free photonic chip offers speed and accuracy for … – Science Daily

Photonic chips have revolutionized data-heavy technologies. On their own or in concert with traditional electronic circuits, these laser-powered devices send and process information at the speed of light, making them a promising solution for artificial intelligence's data-hungry applications.

In addition to their incomparable speed, photonic circuits use significantly less energy than electronic ones. Electrons move relatively slowly through hardware, colliding with other particles and generating heat, while photons flow without losing energy, generating no heat at all. Unburdened by the energy loss inherent in electronics, integrated photonics are poised to play a leading role in sustainable computing.

Photonics and electronics draw on separate areas of science and use distinct architectural structures. Both, however, rely on lithography to define their circuit elements and connect them sequentially. While photonic chips don't make use of the transistors that populate electronic chips' ever-shrinking and increasingly layered grooves, their complex lithographic patterning guides laser beams through a coherent circuit to form a photonic network that can perform computational algorithms.

But now, for the first time, researchers at the University of Pennsylvania School of Engineering and Applied Science have created a photonic device that provides programmable on-chip information processing without lithography, offering the speed of photonics augmented by superior accuracy and flexibility for AI applications.

Achieving unparalleled control of light, this device consists of spatially distributed optical gain and loss. Lasers cast light directly on a semiconductor wafer, without the need for defined lithographic pathways.

Liang Feng, Professor in the Departments of Materials Science and Engineering (MSE) and Electrical Systems and Engineering (ESE), along with Ph.D. student Tianwei Wu (MSE) and postdoctoral fellows Zihe Gao and Marco Menarini (ESE), introduced the microchip in a recent study published in Nature Photonics.

Silicon-based electronic systems have transformed the computational landscape. But they have clear limitations: they are slow in processing signal, they work through data serially and not in parallel, and they can only be miniaturized to a certain extent. Photonics is one of the most promising alternatives because it can overcome all these shortcomings.

"But photonic chips intended for machine learning applications face the obstacles of an intricate fabrication process where lithographic patterning is fixed, limited in reprogrammability, subject to error or damage and expensive," says Feng. "By removing the need for lithography, we are creating a new paradigm. Our chip overcomes those obstacles and offers improved accuracy and ultimate reconfigurability given the elimination of all kinds of constraints from predefined features."

Without lithography, these chips become adaptable data-processing powerhouses. Because patterns are not pre-defined and etched in, the device is intrinsically free of defects. Perhaps more impressively, the lack of lithography renders the microchip impressively reprogrammable, able to tailor its laser-cast patterns for optimal performance, be the task simple (few inputs, small datasets) or complex (many inputs, large datasets).

In other words, the intricacy or minimalism of the device is a sort of living thing, adaptable in ways no etched microchip could be.

"What we have here is something incredibly simple," says Wu. "We can build and use it very quickly. We can integrate it easily with classical electronics. And we can reprogram it, changing the laser patterns on the fly to achieve real-time reconfigurable computing for on-chip training of an AI network."

An unassuming slab of semiconductor, the device couldn't be simpler. It's the manipulation of this slab's material properties that is the key to research team's breakthrough in projecting lasers into dynamically programmable patterns to reconfigure the computing functions of the photonic information processor.

This ultimate reconfigurability is critical for real-time machine learning and AI.

"The interesting part," says Menarini, "is how we are controlling the light. Conventional photonic chips are technologies based on passive material, meaning its material scatters light, bouncing it back and forth. Our material is active. The beam of pumping light modifies the material such that when the signal beam arrives, it can release energy and increase the amplitude of signals."

"This active nature is the key to this science, and the solution required to achieve our lithography-free technology," adds Gao. "We can use it to reroute optical signals and program optical information processing on-chip."

Feng compares the technology to an artistic tool, a pen for drawing pictures on a blank page.

"What we have achieved is exactly the same: pumping light is our pen to draw the photonic computational network (the picture) on a piece of unpatterned semiconductor wafer (the blank page)."

But unlike indelible lines of ink, these beams of light can be drawn and redrawn, their patterns tracing innumerable paths to the future.

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Lithography-free photonic chip offers speed and accuracy for ... - Science Daily

System Overl04d: The Takeover of Artificial Intelligence … – The Southern Digest

The takeover of AI, or artificial intelligence, is a topic of concern for many people. With the rapid advancements in technology, there is a fear that AI could eventually become more intelligent than humans and take over many aspects of our lives.

One of the primary concerns with the takeover of AI is that it could lead to massive job loss. As AI becomes more advanced, it can replace many of the tasks that are currently performed by humans. For example, self-driving cars and trucks could replace the need for human drivers, and automated factories could replace human workers. This could lead to widespread unemployment and economic instability.

Another concern with the takeover of AI is that it could lead to a loss of control. As AI becomes more advanced, it may become more difficult for humans to understand or predict its behavior. This could lead to unintended consequences, such as the creation of autonomous weapons that could cause harm without human intervention. Additionally, there is a fear that AI could become so advanced that it could make decisions on its own, without human oversight.

There is also a concern that the takeover of AI could lead to a loss of privacy. As AI becomes more integrated into our lives, it will have access to a vast amount of data about us. This data could be used to create personalized advertising or to make decisions about our lives without our consent.

Despite these concerns, there are also potential benefits to the takeover of AI. For example, AI could be used to solve many of the world's most pressing problems, such as climate change or disease.

In conclusion, the takeover of AI is a complex and multifaceted issue that requires careful consideration. While there are certainly risks associated with the development of AI, there are also many potential benefits. It is important for us to continue to explore the possibilities of AI while also taking steps to mitigate the risks. By doing so, we can ensure that AI is used in a way that benefits humanity and does not pose a threat to our way of life.

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System Overl04d: The Takeover of Artificial Intelligence ... - The Southern Digest

Why artificial intelligence can’t bring the dead back to life – Fox News

This year is shaping up to be the year of artificial intelligence. ChatGPT has stolen most of the headlines, but it is only the most infamous in a wide assortment AI platforms. One of the most recent to arrive on the scene is HereAfter AI, an app that can "preserve memories with an app that interviews you about your life." The goal: to "let loved ones hear meaningful stories by chatting with the virtual you." Heaven, not in the clouds, but the cloud. Nirvana on your iPhone. Reincarnation through silicon.

The problem is, it wont work. Cant work, in fact.

At this point, no one doubts we can use AI to simulate a generic person, or even a particular person. But this could only ever be a simulation, not the real deal. The reason doesnt have to do with the technical limitations of AI. It rather has to do with the fact that humans are not disembodied souls or pure spirits that could be uploaded to a computer in the first place. Our bodies are not only biological realities--they are a crucial part of who we are.

A couple examples bring the point home: if you are a dancer or an athlete or a musician, you know that when you dance a tango or go in for a layup or run an arpeggio, you think with your body. If you try to think with your head ("first step there, just like so"), youll trip up. Thats why I cant dance I overthink it. Eliminate the body by putting me on an app, and youve eliminated what made me me in the first place.

OPENAI SAYS CHATGPT FEATURE LETTING USERS DISABLE CHAT HISTORY NOW AVAILABLE

Even if it were possible to upload loved ones to a computer, it isnt clear that this would be something we would want. When we lose a loved one, we would do anything to have that person back with us. Thats a natural human desire. But think through what it would mean never to lose anyone, to always have our loved ones in an app, ready for consultation. Not only our parents and grandparents would be part of our lives, but multiple generations of great-grandparents as well. That may be goodit may be, well, strange. But there's no question it would be different than anything we've ever experienced. Imagine the conversations around the Thanksgiving table. Interesting? Absolutely. Something we deeply desire? Not as clear.

There are also problems for HereAfter AI that come directly from how AI is created. To create an AI, one of the first steps is "training": feeding the model massive amounts of data. The model then looks for patterns in these data to transform them into something new. The more training data; the better the model. Thats why Facebook and Twitter and the others are data-hungry: the more data they gather, the better their models become. And it is why ChatGPT is such a powerful form of AI: it was trained on massive amounts of data. As in: all of Wikipedia, millions of ebooks, and snapshots of the entire internet.

Heres the issue: in creating an AI to mimic those weve lost, well need to train the model. How do we do that? HereAfter AI has the answer: feed the model text threads, personal letters, emails, home videos: the list goes on. As with all models, more data means a better model. The closer you come to bringing back someone you love.

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How many of us, though, in attempting to bring back a loved one, would feed HereAfter AI all the snarky things a loved one said? The times grandma didnt give us the benefit of the doubt? The times a spouse spouted conspiracy theories or garbled words or just plain got things wrong? The times a child lied? Not much of that, Im guessing. Train it on the happy times instead.

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But a model, of course, is only as good as its training data. Any "person" weve created using only happy data will be but a shiny veneer of a genuine human being. All of us have bumps and warts, failings and shortcomings, biases, and blindspots. Thats part of being human. Sometimes our shortcomings are our most endearing parts: my family loves me because and not despite my quirks and limitations. Remove the bumps and warts, and you havent created a human at all. Youve instead created a saccharine caricature, dressed in a skin that resembles someone you used to know.

In the Harry Potter series, Albus Dumbledore reflects on Lord Voldemorts quest for immortality: "humans do have a knack for choosing precisely those things that are worst for them." HereAfter AI is no Lord Voldemort, but theyve made the same mistake. Life on an app--for either you or your loved ones--is not heaven. Its not something we even want. What is it? Impossible.

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Why artificial intelligence can't bring the dead back to life - Fox News

Missing persons helped by artificial intelligence – WISH TV Indianapolis, IN

Indiana has been grappling with an unsolved murder and missing person case for years. With the help of revolutionary augmented reality (AR) and artificial intelligence (AI) crime-solving tools, attention is being brought to these cases like never before.

CrimeDoor, the true crime news, and content platform co-founded by Neil Mandt, is using AR pop-ups as a reinvention of the Amber Alert system to provide updates on unsolved cases in the area.

The technology allows users to see virtual pop-ups of information related to each case, making it easier for them to stay informed and potentially provide tips to law enforcement.

As May is known as Missing and Unidentified Persons Month, this technology comes at a crucial time.

According to the National Missing and Unidentified Persons System, over 600,000 people go missing in the United States every year.

This technology has the potential to help solve some of these cases and bring closure to families who have been waiting for answers for years.

Neil Mandt joined us to provide updates on several Indiana cases, including Lauren Spierer, Nakyla Williams, Tatyana Sims, and Marilyn Niqui McCown. These cases have remained unsolved for years, but with the help of AR and AI technology, new leads may be discovered. Watch the full interview above to learn more!

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Missing persons helped by artificial intelligence - WISH TV Indianapolis, IN

Director Chopras Prepared Remarks on the Interagency … – Consumer Financial Protection Bureau

In recent years, we have seen a rapid acceleration of automated decision-making across our daily lives. Throughout the digital world and throughout sectors of the economy, so-called artificial intelligence is automating activities in ways previously thought to be unimaginable.

Generative AI, which can produce voices, images, and videos that are designed to simulate real-life human interactions are raising the question of whether we are ready to deal with the wide range of potential harms from consumer fraud to privacy to fair competition.

Today, several federal agencies are coming together to make one clear point: there is no exemption in our nations civil rights laws for new technologies that engage in unlawful discrimination. Companies must take responsibility for their use of these tools.

The Interagency Statement we are releasing today seeks to take an important step forward to affirm existing law and rein in unlawful discriminatory practices perpetrated by those who deploy these technologies.1

The statement highlights the all-of-government approach to enforce existing laws and work collaboratively on AI risks.

Unchecked AI poses threats to fairness and to our civil rights in ways that are already being felt.

Technology companies and financial institutions are amassing massive amounts of data and using it to make more and more decisions about our lives, including whether we get a loan or what advertisements we see.

While machines crunching numbers might seem capable of taking human bias out of the equation, thats not what is happening. Findings from academic studies and news reporting raise serious questions about algorithmic bias. For example, a statistical analysis of 2 million mortgage applications found that Black families were 80 percent more likely to be denied by an algorithm when compared to white families with similar financial and credit backgrounds. The response of mortgage companies has been that researchers do not have all the data that feeds into their algorithms or full knowledge of the algorithms. But their defense illuminates the problem: artificial intelligence often feels like black boxes behind brick walls.2

When consumers and regulators do not know how decisions are made by artificial intelligence, consumers are unable to participate in a fair and competitive market free from bias.

Thats why the CFPB and other agencies are prioritizing and confronting digital redlining, which is redlining caused through bias present in lending or home valuation algorithms and other technology marketed as artificial intelligence. They are disguised through so-called neutral algorithms, but they are built like any other AI system by scraping data that may reinforce the biases that have long existed.

We are working hard to reduce bias and discrimination when it comes to home valuations, including algorithmic appraisals. We will be proposing rules to make sure artificial intelligence and automated valuation models have basic safeguards when it comes to discrimination.

We are also scrutinizing algorithmic advertising, which, once again, is often marketed as AI advertising. We published guidance to affirm how lenders and other financial providers need to take responsibility for certain advertising practices. Specifically, advertising and marketing that uses sophisticated analytic techniques, depending on how these practices are designed and implemented, could subject firms to legal liability.

Weve also taken action to protect the public from black box credit models in some cases so complex that the financial firms that rely on them cant even explain the results. Companies are required to tell you why you were denied for credit and using a complex algorithm is not a defense against providing specific and accurate explanations.

Developing methods to improve home valuation, lending, and marketing are not inherently bad. But when done in irresponsible ways, such as creating black box models or not carefully studying the data inputs for bias, these products and services pose real threats to consumers civil rights. It also threatens law-abiding nascent firms and entrepreneurs trying to compete with those who violate the law.

I am pleased that the CFPB will continue to contribute to the all-of-government mission to ensure that the collective laws we enforce are followed, regardless of the technology used.

Thank you.

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Director Chopras Prepared Remarks on the Interagency ... - Consumer Financial Protection Bureau