hilosopher Shannon Vallor and I are in the British Library in London, home to 170 million items—books, recordings, newspapers, manuscripts, maps. In other words, we’re talking in the kind of place where today’s artificial intelligence chatbots like ChatGPT come to feed. Sitting on the library’s café balcony, we are literally in the shadow of the Crick Institute, the biomedical research hub where the innermost mechanisms of the human body are studied. If we were to throw a stone from here across St. Pancras railway station, we might hit the London headquarters of Google, the company for which Vallor worked as an AI ethicist before moving to Scotland to head the Center for Technomoral Futures at the University of Edinburgh. Here, wedged between the mysteries of the human, the embedded cognitive riches of human language, and the brash swagger of commercial AI, Vallor is helping me make sense of it all. Will AI solve all our problems, or will it make us obsolete, perhaps to the point of extinction? Both possibilities have engendered hyperventilating headlines. Vallor has little time for either. She acknowledges the tremendous potential of AI to be both beneficial and destructive, but she thinks the real danger lies elsewhere. As she explains in her 2024 book , both the starry-eyed notion that AI thinks like us and the paranoid fantasy that it will manifest as a malevolent dictator, assert a fictitious kinship with humans at the cost of creating a naïve and toxic view of how our own minds work. It’s a view that could encourage us to relinquish our agency and forego our wisdom in deference to the machines. It’s easy to assert kinship between machines and humans when humans are seen as mindless machines. Reading I was struck by Vallor’s determination to probe more deeply than the usual litany of concerns about AI: privacy, misinformation, and so forth. Her book is really a discourse on the relation of human and machine, raising the alarm on how the tech industry propagates a debased version of what we are, one that reimagines the human in the guise of a soft, wet computer. If that sounds dour, Vallor most certainly isn’t. She wears lightly the deep insight gained from seeing the industry from the inside, coupled to a grounding in the philosophy of science and technology. She is no crusader against the commerce of AI, speaking warmly of her time at Google while laughing at some of the absurdities of Silicon Valley. But the moral and intellectual clarity and integrity she brings to the issues could hardly offer a greater contrast to the superficial, callow swagger typical of the proverbial tech bros. “We’re at a moment in history when we need to rebuild our confidence in the capabilities of humans to reason wisely, to make collective decisions,” Vallor tells me. “We’re not going to deal with the climate emergency or the fracturing of the foundations of democracy unless we can reassert a confidence in human thinking and judgment. And everything in the AI world is working against that.” To understand AI algorithms, Vallor argues we should not regard them as minds. “We’ve been trained over a century by science fiction and cultural visions of AI to expect that when it arrives, it’s going to be a machine mind,” she tells me. “But what we have is something quite different in nature, structure, and function.” Rather, we should imagine AI as a mirror, which doesn’t duplicate the thing it reflects. “When you go into the bathroom to brush your teeth, you know there isn’t a second face looking back at you,” Vallor says. “That’s just a reflection of a face, and it has very different properties. It doesn’t have warmth; it doesn’t have depth.” Similarly, a reflection of a mind is not a mind. AI chatbots and image generators based on large language models are of human performance. “With ChatGPT, the output you see is a reflection of human intelligence, our creative preferences, our coding expertise, our voices—whatever we put in.” Even experts, Vallor says, get fooled inside this hall of mirrors. Geoffrey Hinton, the computer scientist who shared this year’s Nobel Prize in physics for his pioneering work in developing the deep-learning techniques that made LLMs possible, at an AI conference in 2024 that “we understand language in much the same way as these large language models.” Hinton is convinced these forms of AI don’t just blindly regurgitate text in patterns that seem meaningful to us; they develop some sense of the meaning of words and concepts themselves. An LLM is trained by allowing it to adjust the connections in its neural network until it reliably gives good answers, a process that Hinton to “parenting for a supernaturally precocious child.” But because AI can “know” vastly more than we can, and “thinks” much faster, Hinton concludes that it might ultimately supplant us: “It’s quite conceivable that humanity is just a passing phase in the evolution of intelligence,” at a 2023 MIT Technology Review conference. “Hinton is so far out over his skis when he starts talking about knowledge and experience,” Vallor says. “We know that the are only superficially analogous in their structure and function. In terms of what’s happening at the physical level, there’s a gulf of difference that we have every reason to think makes a difference.” There’s no real kinship at all. I agree that apocalyptic claims have been given far too much airtime, I say to Vallor. But some researchers say LLMs are getting more “cognitive”: OpenAI’s latest chatbot, model o1, is said to work via a series of chain-of-reason steps (even though the company won’t disclose them, so we can’t know if they resemble human reasoning). And AI surely does have features that can be considered aspects of mind, such as memory and learning. Computer scientist Melanie Mitchell and complexity theorist r have that, while we shouldn’t regard these systems as minds like ours, they might be considered minds of a quite different, unfamiliar variety. “I’m quite skeptical about that approach. It might be appropriate in the future, and I’m not opposed in principle to the idea that we might build machine minds. I just don’t think that’s what we’re doing right now.” Vallor’s resistance to the idea of stems from her background in philosophy, where mindedness tends to be rooted in experience: precisely what today’s AI does not have. As a result, she says, it isn’t appropriate to speak of these machines as thinking. Her view collides with the 1950 paper by British mathematician and computer pioneer Alan Turing, “Computing machinery and Intelligence,” often regarded as the conceptual foundation of AI. Turing asked the question: “Can machines think?”—only to replace it with what he considered to be a better question, which was whether we might develop machines that could give responses to questions we’d be unable to distinguish from those of humans. This was Turing’s “ ,” now commonly known as the Turing test. But imitation is all it is, Vallor says. “For me, thinking is a specific and rather unique set of experiences we have. Thinking without experience is like water without the hydrogen—you’ve taken something out that loses its identity.” Reasoning requires concepts, Vallor says, and LLMs don’t those. “Whatever we’re calling concepts in an LLM are actually something different. It’s a statistical mapping of associations in a high-dimensional mathematical vector space. Through this representation, the model can get a line of sight to the solution that is more efficient than a random search. But that’s not how we think.” They are, however, very good at . “We can ask the model, ‘How did you come to that conclusion?’ and it just bullshits a whole chain of thought that, if you press on it, will collapse into nonsense very quickly. That tells you that it wasn’t a train of thought that the machine followed and is committed to. It’s just another probabilistic distribution of reason-like shapes that are appropriately matched with the output that it generated. It’s entirely post hoc.” The pitfall of insisting on a fictitious kinship between the human mind and the machine can be discerned since the earliest days of AI in the 1950s. And here’s what worries me most about it, I tell Vallor. It’s not so much because the capabilities of the AI systems are being overestimated in the comparison, but because the way the human brain works is being so diminished by it. “That’s my biggest concern,” she agrees. Every time she gives a talk pointing out that AI algorithms are not really minds, Vallor says, “I’ll have someone in the audience come up to me and say, ‘Well, you’re right but only because at the end of the day our minds aren’t doing these things either—we’re not really rational, we’re not really responsible for what we believe, we’re just predictive machines spitting out the words that people expect, we’re just matching patterns, we’re just doing what an LLM is doing.’” Hinton has suggested an LLM can have feelings. “Maybe not exactly as we do but in a slightly different sense,” Vallor says. “And then you realize he’s only done that by stripping the concept of emotion from anything that is humanly experienced and turning it into a behaviorist reaction. It’s taking the most reductive 20th-century theories of the human mind as baseline truth. From there it becomes very easy to assert kinship between machines and humans because you’ve already turned the human into a mindless machine.” It’s with the much-vaunted notion of artificial general intelligence (AGI) that these problems start to become acute. AGI is often defined as a machine intelligence that can perform any intelligent function that humans can, but better. Some believe we are already on that threshold. Except that, to make such claims, we must redefine human intelligence as a subset of what we do. “Yes, and that’s a very deliberate strategy to draw attention away from the fact that we haven’t made AGI and we’re nowhere near it,” Vallor says. Silicon Valley culture has the features of religion. It’s unshakeable by counterevidence or argument. Originally, AGI meant something that misses nothing of what a human mind could do—something about which we’d have no doubt that it is thinking and understanding the world. But in , Vallor explains that experts such as Hinton and Sam Altman, CEO of OpenAI, the company that created ChatGPT, now define AGI as a system that is equal to or better than humans at calculation, prediction, modeling, production, and problem-solving. “In effect,” Vallor says, Altman “moved the goalposts and said that what we mean by AGI is a machine that can in effect do all of the economically valuable tasks that humans do.” It’s a common view in the community. Mustafa Suleyman, CEO of Microsoft AI, has written the ultimate objective of AI is to “distill the essence of what makes us humans so productive and capable into software, into an algorithm,” which he considers equivalent to being able to “replicate the very thing that makes us unique as a species, our intelligence.” When she saw Altman’s reframing of AGI, Vallor says, “I had to shut the laptop and stare into space for half an hour. Now all we have for the target of AGI is something that your boss can replace you with. It can be as mindless as a toaster, as long as it can do your work. And that’s what LLMs are—they are mindless toasters that do a lot of cognitive labor without thinking.” I probe this point with Vallor. After all, having AIs that can beat us at chess is one thing—but now we have algorithms that write convincing prose, have engaging chats, make music that fools some into thinking it was made by humans. Sure, these systems can be rather limited and bland—but aren’t they encroaching ever more on tasks we might view as uniquely human? “That’s where the mirror metaphor becomes helpful,” she says. “A mirror image can dance. A good enough mirror can show you the aspects of yourself that are deeply human, but not the inner experience of them—just the performance.” With AI art, she adds, “The important thing is to realize there’s nothing on the other side participating in this communication.” What confuses us is we can feel emotions in response to an AI-generated “work of art.” But this isn’t surprising because the machine is reflecting back permutations of the patterns that humans have made: Chopin-like music, Shakespeare-like prose. And the emotional response isn’t somehow encoded in the stimulus but is constructed in our own minds: Engagement with art is far less passive than we tend to imagine. But it’s not just about art. “We are meaning-makers and meaning-inventors, and that’s partly what gives us our personal, creative, political freedoms,” Vallor says. “We’re not locked into the patterns we’ve ingested but can rearrange them in new shapes. We do that when we assert new moral claims in the world. But these machines just recirculate the same patterns and shapes with slight statistical variations. They do not have the capacity to make meaning. That’s fundamentally the gulf that prevents us being justified in claiming real kinship with them.” I ask Vallor whether some of these misconceptions and misdirection about AI are rooted in the nature of the tech community itself—in its narrowness of training and culture, its lack of diversity. She sighs. “Having lived in the San Francisco Bay Area for most of my life and having worked in tech, I can tell you the influence of that culture is profound, and it’s not just a particular cultural outlook, . There are certain commitments in that way of thinking that are unshakeable by any kind of counterevidence or argument.” In fact, providing counterevidence just gets you excluded from the conversation, Vallor says. “It’s a very narrow conception of what intelligence is, driven by a very narrow profile of values where efficiency and a kind of winner-takes-all domination are the highest values of any intelligent creature to pursue.” But this efficiency, Vallor continues, “is never defined with any reference to any higher value, which always slays me. Because I could be the most efficient at burning down every house on the planet, and no one would say, ‘Yay Shannon, you are the most efficient pyromaniac we have ever seen! Good on you!’” People really think the sun is setting on human decision-making. That’s terrifying to me. In Silicon Valley, efficiency is an end in itself. “It’s about achieving a situation where the problem is solved and there’s no more friction, no more ambiguity, nothing left unsaid or undone, you’ve dominated the problem and it’s gone and all there is left is your perfect shining solution. It is this ideology of intelligence as a thing that wants to remove the business of thinking.” Vallor tells me she once tried to explain to an AGI leader that there’s no mathematical solution to the problem of justice. “I told him the nature of justice is we have conflicting values and interests that cannot be made commensurable on a single scale, and that the work of human deliberation and negotiation and appeal is essential. And he told me, ‘I think that just means you’re bad at math.’ What do you say to that? It becomes two worldviews that don’t intersect. You’re speaking to two very different conceptions of reality.” Vallor doesn’t underestimate the threats that ever-more powerful AI presents to our societies, from our privacy to misinformation and political stability. But her real worry right now is what AI is doing to our notion of ourselves. “I think AI is posing a fairly imminent threat to the existential significance of human life,” Vallor says. “Through its automation of our thinking practices, and through the narrative that’s being created around it, AI is undermining our sense of ourselves as responsible and free intelligences in the world. You can find that in authoritarian rhetoric that wishes to justify the deprivation of humans to govern themselves. That story has had new life breathed into it by AI.” Worse, she says, this narrative is presented as an objective, neutral, politically detached story: It’s just . “You get these people who really think that the time of human agency has ended, the sun is setting on human decision-making—and that that’s a good thing and is simply scientific fact. That’s terrifying to me. We’re told that what’s next is that AGI is going to build something better. And I do think you have very cynical people who believe this is true and are taking a kind of religious comfort in the belief that they are shepherding into existence our machine successors.” Vallor doesn’t want AI to come to a halt. She says it really could help to solve some of the serious problems we face. “There are still huge applications of AI in medicine, in the energy sector, in agriculture. I want it to continue to advance in ways that are wisely selected and steered and governed.” That’s why a backlash against it, however understandable, could be a problem in the long run. “I see lots of people turning against AI,” Vallor says. “It’s becoming a powerful hatred in many creative circles. Those communities were much more balanced in their attitudes about three years ago, when LLMs and image models started coming out. There were a lot of people saying, ‘This is kind of cool.’ But the approach by the AI industry to the rights and agency of creators has been so exploitative that you now see creatives saying, ‘Fuck AI and everyone attached to it, don’t let it anywhere near our creative work.’ I worry about this reactive attitude to the most harmful forms of AI spreading to a general distrust of it as a path to solving any kind of problem.” While Vallor still wants to promote AI, “I find myself very often in the camp of the people who are turning angrily against it for reasons that are entirely legitimate,” she says. That divide, she admits, becomes part of an “artificial separation people often cling to between humanity and technology.” Such a distinction, she says, “is potentially quite damaging, because technology is fundamental to our identity. We’ve been technological creatures since before we were . Tools have been instruments of our liberation, of creation, of better ways of caring for one another and other life on this planet, and I don’t want to let that go, to enforce this artificial divide of humanity versus the machines. Technology at its core can be as humane an activity as anything can be. We’ve just lost that connection.” Posted on Philip Ball is a freelance writer based in London, and the author of many books on science and its interactions with the broader culture. His latest book is . Cutting-edge science, unraveled by the very brightest living thinkers.
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Xavier tries to get right vs. Morgan State before rivalry clash
Trump selects longtime adviser Keith Kellogg as special envoy for Ukraine and Russia
Donald Trump to ring New York Stock Exchange bell as Time names him Person of the YearSpeaking in a recent episode of 'Inside the NBA,' basketball legend Charles Barkley spoke up about LeBron James and the NBA's GOAT debate. According to Chuck, there isn't even an argument for LeBron given all that Michael accomplished during his time in the league. Ernie Johnson: "LeBron is 2nd in 30-point games with 559, Jordan has 562." Charles Barkley: "LeBron has played how many more seasons than MJ and he's still behind him that's crazy. I love LeBron but for him to be that far behind MJ and he's played eight more seasons? C'mon man, y'all need to stop this." Charles Barkley on Lebron being called the GOAT over MJ: Ernie: "Lebron is 2nd in 30pt games with 559, MJ has 562" Charles: "Lebron has played how many more seasons than MJ and hes still behind him thats crazy, yall need to stop this" Lebron is nothing but a stat padding... pic.twitter.com/WWHCaFo2CE We all know that LeBron is the king of longevity and after 21 years in the NBA, it's no surprise when he breaks a record that involves racking up the stats. With 559 30-point games for his career, one might think that LeBron James is the leader of that category but somehow, Michael still holds the top spot with 562 30-point games in much less time. This point is just one countless to be made on the debate surrounding LeBron James and Michael Jordan. As two of the greatest NBA legends, they are always being compared and fans are always discussing which one is more successful than the other. As a whole, the NBA GOAT debate has been raging for decades now, and Michael Jordan has been leading the conversation ever since his rise to power in the early 90s. On the court, the Bulls legend was absolutely unstoppable, and his unmatched skills, athleticism, and drive made him one of the biggest stars in basketball history. From 1984 to 2003, Jordan took the NBA by storm with 6 championships, 5 MVPs, 10 scoring titles, and 14 All-Star appearances. For his career, Michael averaged 30.1 points, 6.2 rebounds, and 5.3 assists per game on 49.7% shooting. With his career, LeBron James has come closer than anyone else to surpassing Jordan's legacy but he still has a ways to go. As a 4x champion, 4x MVP, James falls behind in several key categories despite playing almost twice as long as the Bulls superstar. It makes sense that LeBron, who frequently likes to take on more of a playmaking role, would score at a slower rate than Jordan --- but after 21 years, you'd expect LeBron to be way ahead of anyone when it comes to putting the ball through the net, especially as the NBA's all-time leading scorer. Instead, the numbers show that while LeBron has been scoring for longer, Michael scored with more frequency throughout his career and it's that same aggressive approach to the game that helped him have such a commanding presence on the court. So, while LeBron James may own the record books when it's all said and done, the fact that it took him this long to catch up says a lot about Jordan and how far ahead he was for his time. If his career was as long and durable as LeBron's, there would be no question that he's the GOAT but advances in sports medicine aren't nearly what they are now and we'll never get the chance to see it for ourselves. Related: De'Aaron Fox Declares LeBron James As His GOAT Over Michael Jordan Thank you for being a valued reader of Fadeaway World. If you liked this article, please consider following us on Google News . We appreciate your support.
US Supreme Court tosses case involving securities fraud suit against Nvidia
Is it safe to eat turkey this Thanksgiving amid bird flu outbreak? Here’s what experts sayTrump selects longtime adviser Keith Kellogg as special envoy for Ukraine and RussiaIs it safe to eat turkey this Thanksgiving amid bird flu outbreak? Here’s what experts sayContent Intelligence Market Revenues Anticipated to Increase Significantly Due to High Demand by 2024-2031 | Emplifi Inc., OpenText Corp., Microsoft Corporation, Adobe Inc
NoneFormer Tulane quarterback Darian Mensah has already found a new program in Duke, while Mississippi State's Michael Van Buren Jr., Wisconsin's Braedyn Locke and Cal's Fernando Mendoza are exploring changes of their own in the transfer portal. Mensah, a redshirt freshman with three years of eligibility remaining, told ESPN on Wednesday he has transferred to Duke. He attended the Blue Devils men's basketball game against Incarnate Word on Tuesday night. The Blue Devils (9-3) will face Mississippi in the Gator Bowl, but without 2024 starting quarterback Maalik Murphy and backup Grayson Loftis, who also entered the portal. Mensah, viewed as one of the top players in the portal, threw for 2,723 yards and 22 touchdowns and completed 65.9% of his passes. He led the Green Wave to a 9-4 record and the American Athletic Conference championship game, where they lost 35-14 to Army. Tulane will play Florida in the Gasparilla Bowl on Sunday. Van Buren, Mendoza and Locke announced on social media they had entered the portal. Van Buren started eight games as a true freshmen for the Bulldogs. He threw for 1,886 yards on 55% passing with 16 total touchdowns and seven interceptions for the Bulldogs (2-10, 0-8 Southeastern Conference). He took over as the starter when Blake Shapen suffered a season-ending shoulder injury in a 45-28 loss to Florida on Sept. 21. Shapen has said he plans to return next season. Van Buren, a 6-foot-1, 200-pound passer from St. Frances Academy in Maryland, had two 300-yard performances for the Bulldogs, including 306 yards and three touchdown passes in a 41-31 road loss against Georgia. Mendoza threw for 3,004 yards in 2024 with 16 TDs, six interceptions and a 68.7 completion percentage. "For the sake of my football future this is the decision I have reached," he posted. Locke passed for 1,936 yards with 13 touchdowns and 10 interceptions for Wisconsin this season. He said he will have two years of eligibility remaining at his next school. ANN ARBOR, Mich. — Michigan cornerback Will Johnson has joined defensive tackle Mason Graham in the NFL draft. Johnson declared for the draft on Wednesday, one day after Graham decided he would also skip his senior season with the Wolverines. Both preseason All-America players are expected to be first-round picks. Johnson was limited to six games this year due to an injury. He had two interceptions, returning them both for touchdowns to set a school record with three scores off interceptions. Johnson picked off nine passes in three seasons. Graham played in all 12 games this season, finishing with 3 1/2 sacks and seven tackles for losses. He had 18 tackles for losses, including nine sacks, in his three-year career. Tennessee running back Dylan Sampson is The Associated Press offensive player of the year in the Southeastern Conference and South Carolina defensive lineman Kyle Kennard is the top defensive player. Vanderbilt quarterback Diego Pavia was voted the top newcomer on Wednesday while the Gamecocks' Shane Beamer is coach of the year in voting by the panel of 17 media members who cover the league. Sampson led the SEC and set school records by rushing for 1,485 yards and 22 touchdowns. He is tied for third nationally in rushing touchdowns, recording the league's fifth-most in a season. Sampson was chosen on all but two ballots. Mississippi wide receiver Tre Harris and his quarterback, Jaxson Dart, each got a vote. Kennard led the SEC with 11-1/2 sacks and 15-1/2 tackles for loss. He also had 10 quarterback hurries and forced three fumbles. Beamer led the Gamecocks to just their fifth nine-win season, including a school-record four wins over Top 25 opponents. They've won their last six games and ended the regular season with a win over eventual ACC champion Clemson. South Carolina plays Illinois on Dec. 31 in the Citrus Bowl. Pavia helped lead Vandy to its first bowl game since 2018 after transferring from New Mexico State. He passed for 2,133 yards and 17 touchdowns with four interceptions. He ran for another 716 yards and six touchdowns, directing an upset of Alabama. AMES, Iowa — Matt Campbell, who led Iowa State to its first 10-win season and became the program's all-time leader in coaching victories, has agreed to an eight-year contract that would keep him with the Cyclones through 2032. University president Wendy Wintersteen and athletic director Jamie Pollard made the announcement Wednesday, four days after the Cyclones lost to Arizona State in the Big 12 championship game. “Given all the uncertainty currently facing college athletics, it was critical that we moved quickly to solidify the future of our football program,” Pollard said. “Matt is the perfect fit for Iowa State University and I am thrilled he wants to continue to lead our program. Leadership continuity is essential to any organization’s long-term success." The Cyclones won their first seven games for their best start since 1938 and are 10-3 heading into their game against Miami in the Pop Tarts Bowl in Orlando, Florida, on Dec. 28. BRIEFLY FLAG PLANT: Ohio Republican state Rep. Josh Williams said Wednesday on social media he's introducing a bill to make flag planting in sports a felony in the state. His proposal comes after the Nov. 30 fight at the Michigan-Ohio State rivalry football game when the Wolverines beat the Buckeyes 13-10 and then attempted to plant their flag at midfield. MALZAHN: Gus Malzahn, who resigned as UCF’s coach last month to become Mike Norvell’s offensive coordinator at Florida State, said he chose to return to his coaching roots rather than remain a head coach distracted by a myriad of responsibilities. Get local news delivered to your inbox!This new year, instant social media wishes leave greeting cards in the dust
Secure Multiparty Computation Market Growth Size, Opportunities, Future Scope, Business Scenario, Share, Key Segments And Forecast To 2029 12-11-2024 10:28 PM CET | Business, Economy, Finances, Banking & Insurance Press release from: ABNewswire Microsoft (US), IBM (US), Google (US), Fireblocks (US), Blockdaemon (US), Qredo (British Virgin Islands), Penta Security (South Korea), Zengo (Israel), Inpher (US), CYBAVO (Singapore), Liminal Custody (Singapore), Spatium (Singapore), Silence Laboratories Secure Multiparty Computation (SMPC) Market by Offering (Solutions and Services), Deployment Mode (Cloud and On-premises), Vertical (BFSI, IT & ITeS, Government, Healthcare, and Retail & E-commerce) and Region - Global Forecast to 2029. The global secure multiparty computation (SMPC) market [ https://www.marketsandmarkets.com/Market-Reports/secure-multiparty-computation-market-67797344.html?utm_campaign=securemultipartycomputationmarket&utm_source=abnewswire.com&utm_medium=paidpr ] is expected to grow from USD 824 million in 2024 to USD 1.412 billion by 2029, registering a Compound Annual Growth Rate (CAGR) of 11.4% during the forecast period. This growth is driven by the rising demand for private key security enabled by SMPC and the increasing emphasis on compliance with data privacy regulations. Download PDF Brochure@ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=67797344 [ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=67797344&utm_campaign=securemultipartycomputationmarket&utm_source=abnewswire.com&utm_medium=paidpr ] Based on the deployment mode, cloud deployment to grow at the highest CAGR during the forecast period. Cloud-based SMPC fosters secure collaboration while adhering to data privacy regulations and keeping sensitive information within each party's control. Cloud providers handle the infrastructure and software maintenance, freeing up an organization's IT resources to focus on core competencies. Automatic updates and security patches ensure the system stays current with the latest advancements. The integration of Cloud SMPC with other emerging technologies, such as AI and machine learning, is opening up new possibilities. For example, secure multi-party machine learning models can be trained on sensitive data from different sources without compromising privacy. By vertical, healthcare accounts for the highest market size during the forecast period. SMPC holds immense potential for revolutionizing healthcare by safeguarding sensitive patient data while enabling collaborative analysis and research. In the healthcare sector, where privacy and data security are paramount, MPC offers a groundbreaking solution. This technology facilitates secure collaborations among healthcare institutions, researchers, and practitioners, leading to advancements in medical research, diagnosis, treatment, and public health initiatives. Additionally, MPC fosters trust among patients by assuring them that their personal health information remains protected. With SMPC, healthcare stakeholders can leverage collective insights from diverse datasets without compromising individual privacy, ultimately driving innovation and improving patient outcomes. By region, Asia Pacific is to grow at the highest CAGR during the forecast period. The Asia Pacific region is growing at the fastest rate in the SMPC market due to several key factors driving the demand for secure computation. Rapid economic growth and technological advancements, particularly in blockchain technology and digital wallets, necessitate efficient computation of data, prompting the adoption of SMPC. Asia Pacific's diverse and interconnected markets require secure methods for cross-border data collaboration. SMPC facilitates secure data sharing and joint computations between organizations in different countries, supporting regional economic integration. These factors collectively contribute to the rapid growth of the SMPC market in the Asia Pacific region, positioning it as a frontrunner in the adoption of integrated security solutions. Request Sample Pages@ https://www.marketsandmarkets.com/requestsampleNew.asp?id=67797344 [ https://www.marketsandmarkets.com/requestsampleNew.asp?id=67797344&utm_campaign=securemultipartycomputationmarket&utm_source=abnewswire.com&utm_medium=paidpr ] Unique Features in the Secure Multiparty Computation Market SMPC enables multiple parties to jointly compute functions over their inputs while keeping those inputs private. This capability is crucial for sensitive data handling in applications such as financial analysis, healthcare, and research, ensuring data confidentiality throughout the process. The market is built on advanced cryptographic techniques, such as secret sharing and homomorphic encryption. These ensure robust security by preventing unauthorized access or data breaches during computations. SMPC solutions are designed to scale efficiently with increasing participants and data volumes. They are adaptable to various use cases, including distributed data analysis, secure voting systems, and collaborative machine learning. By eliminating the need for a central trusted authority, SMPC facilitates decentralized processing. This approach reduces the risk of single points of failure, ensuring enhanced reliability and trust in the system. SMPC solutions align with stringent data privacy regulations such as GDPR, HIPAA, and CCPA. They allow organizations to process sensitive information securely while maintaining compliance with legal requirements. Major Highlights of the Secure Multiparty Computation Market As organizations prioritize data privacy and confidentiality, the adoption of SMPC solutions is on the rise. These technologies enable secure collaboration and computation, addressing concerns over sensitive data handling without compromising privacy. The growing complexity of data protection regulations, such as GDPR, HIPAA, and CCPA, is driving the demand for SMPC. These solutions provide organizations with a secure means of meeting compliance requirements while processing sensitive data. SMPC is gaining traction in various sectors, including finance, healthcare, government, and telecommunications. Its ability to facilitate secure multiparty collaboration makes it ideal for use cases such as fraud detection, secure voting, and privacy-preserving analytics. Continuous innovation in cryptographic methods, such as secret sharing, zero-knowledge proofs, and homomorphic encryption, is enhancing the efficiency and scalability of SMPC solutions. These advancements are reducing computational overhead and improving usability. The convergence of SMPC with blockchain, artificial intelligence (AI), and Internet of Things (IoT) technologies is opening new avenues for secure data processing. These integrations enhance functionality and broaden the scope of SMPC applications. Inquire Before Buying@ https://www.marketsandmarkets.com/Enquiry_Before_BuyingNew.asp?id=67797344 [ https://www.marketsandmarkets.com/Enquiry_Before_BuyingNew.asp?id=67797344&utm_campaign=securemultipartycomputationmarket&utm_source=abnewswire.com&utm_medium=paidpr ] Top Companies in the Secure Multiparty Computation Market The secure multiparty computation market is led by some of the globally established players, such as Microsoft (US), IBM (US), Google (US), Fireblocks (US), Blockdaemon (US), Qredo (British Virgin Islands), Penta Security (South Korea), Zengo (Israel), Inpher (US), CYBAVO (Singapore). Partnerships, agreements, collaborations, acquisitions, and product developments are some of the various growth strategies these players use to increase their market presence. Google is a multinational technology provider that operates on both advertising and subscription models, funding free services like search, email, and maps through targeted ads, while also providing premium subscriptions for cloud storage via Google Drive and business tools through Google Workspace. The company's extensive product portfolio includes productivity tools within Google Workspace, Google Meet for video conferencing, the Chrome web browser, and hardware such as Pixel smartphones, Chromebooks, and Nest smart home devices. In SMPC, Google Cloud Platform (GPC) provides the necessary infrastructure and tools that can be leveraged to build and deploy secure multiparty computation solutions. It allows to scale SMPC solutions based on specific needs. Microsoft is a software provider company that offers a comprehensive range of products and services including software, and hardware products. Their business model relies on a mix of licensing and subscriptions. Microsoft Azure provides the tools and infrastructure needed to build custom SMPC solutions. Organizations can leverage Azure's scalable cloud resources to deploy SMPC protocols tailored to their specific needs, facilitating secure collaborative computations across various use cases. Azure's ecosystem includes partnerships with leading cybersecurity and cryptographic research institutions. This collaboration fosters the development and integration of advanced SMPC techniques, ensuring Azure stays at the forefront of secure data processing technologies. Penta Security Systems Inc. is a leading provider of cybersecurity solutions and services. Established in 1997, Penta Security specializes in offering advanced web application firewall (WAF), data encryption, and authentication technologies. The company's flagship product, WAPPLES, is renowned for its robust protection against web-based cyber threats, including DDoS attacks and OWASP Top 10 vulnerabilities. Penta Security serves a wide range of industries, including finance, healthcare, telecommunications, and government sectors, ensuring data security and regulatory compliance. With a strong focus on innovation and customer satisfaction, Penta Security continues to expand its global footprint, providing cutting-edge cybersecurity solutions to protect organizations from evolving cyber threats. Zengo is a cybersecurity startup focused on providing solutions to protect cryptocurrency assets. Founded in 2018, Zengo offers a non-custodial wallet that combines simplicity with high security standards. Their wallet uses a novel cryptographic technique called threshold signatures, which enhances security by distributing private key fragments across multiple devices without compromising usability. This approach aims to eliminate the risks associated with traditional cryptocurrency wallets, such as phishing attacks and key theft. Zengo's mission is to make cryptocurrency management more accessible and secure for users, leveraging cutting-edge technology to protect digital assets effectively. CYBAVO is a cybersecurity company based in Singapore, specializing in providing secure digital asset management solutions for cryptocurrency exchanges, custodians, and financial institutions. Founded in 2018, CYBAVO focuses on enhancing the security and usability of cryptocurrency storage and transactions through its comprehensive suite of products. These include secure wallet management solutions, multi-signature wallet services, and blockchain infrastructure security. CYBAVO's solutions are designed to protect against various cyber threats, ensuring the integrity and confidentiality of digital assets. The company serves clients globally, aiming to set industry standards for secure cryptocurrency storage and management. Media Contact Company Name: MarketsandMarkets Trademark Research Private Ltd. Contact Person: Mr. Rohan Salgarkar Email:Send Email [ https://www.abnewswire.com/email_contact_us.php?pr=secure-multiparty-computation-market-growth-size-opportunities-future-scope-business-scenario-share-key-segments-and-forecast-to-2029 ] Phone: 18886006441 Address:1615 South Congress Ave. Suite 103, Delray Beach, FL 33445 City: Florida State: Florida Country: United States Website: https://www.marketsandmarkets.com/Market-Reports/secure-multiparty-computation-market-67797344.html This release was published on openPR.
The United States is a paradox: Media and public opinion polls portray us as a nation divided along partisan lines, but deeper research reveals that Americans share common ground on many core values and political issues. As a political philosopher , I worry about the growing chasm between our shared concerns and the often ugly polarization that divides the electorate. As we gather with family and friends who may have voted for different candidates this Thanksgiving, let’s keep in mind the many things we do agree on. A fuller awareness of our shared principles – particularly on what are so often presented as divisive policy issues – can help us listen to and respect one another over the dinner table conversation, even if it turns to politics. Cultivating political civility and unity in our private lives is a modest yet indispensable act that we all can undertake to defend and nurture the norms and culture of democracy – even if some of our political representatives fail to set the same example in public life. For starters, there is huge agreement among Americans on issues such as taxes, immigration and the economy, a 2023 survey by the American Communities Project found . There is also strong support for fundamental democratic principles , including equal protection under the law, voting rights and our First Amendment freedoms of religion, assembly, speech and the press. Judy Ho Oct. 29, 2024 In survey after survey, a majority of Americans say abortion should be legal in most or all cases. There is also broad support for high-quality health care that is accessible to all . A majority of U.S. citizens acknowledge the reality of human-caused climate change and endorse the development of renewable energy , though they may differ on how to achieve those goals. Too often positions are treated as adversarial when in fact they can be compatible – and voters with nuanced views may actually hold both positions. For example, there is broad support for stronger gun control regulations , as well as support for the right to bear arms. For all the bitterness of the 2024 presidential election, the top concerns were widely shared across party lines. Both Republicans and Democrats ranked the economy as a top political priority. A shared pessimism over the economy clearly helped Donald Trump win the election. On immigration, another key factor in the election, Americans have a positive view of legal immigration , though that sentiment has declined in recent years . Today, most Americans want to see immigration reduced . Part of the tension in the nation’s thinking about immigration stems from a political culture that is more responsive to sensationalism and disinformation than to sober consideration and discussion of the pros and cons of immigration. Much of the discourse was marred by fictional and bigoted tales of immigrants eating pets and false portrayals of most immigrants as criminals . Even shared political perceptions aren’t always based on good evidence or reasons. Despite sharing common ground, Americans perceive the nation as deeply polarized , and constant exposure to disinformation makes it nearly impossible to sort fact from fiction. Indeed, the perception of division can itself fuel distrust where commonality might otherwise be found. This perception of polarization can be exploited by partisans with something to gain. When people are told that experts are divided on an issue, such as climate change, it leads to distrust and polarization . Conversely, emphasizing scientific consensus tends to unify public concern and action. The perception that Americans are more divided than we are poses an enormous threat to democracy. People begin to see even neighbors and family members who vote differently as enemies rather than fellow citizens. Stress about holiday interactions with relatives who voted differently is leading some people to cancel family gatherings rather than spend time together. If people are too busy attacking each other, they will miss opportunities to unite, and they will fail to recognize the real threats to their shared values. Johnny C. Taylor Jr. July 19, 2024 Recognizing the public’s shared values is an important first step in healing political divides. Philosopher Robert B. Talisse has argued that one way to get started might be refocusing attention on nonpolitical community projects that bring together people who don’t normally think of each other as allies. That includes civic or sports clubs and local community events. These are collaborative in a way that supports community identity rather than partisan identity. It is an exercise in rebuilding civic trust and recognizing each other as fellow citizens, and perhaps even friends, without the tension of partisan politics. Once this trust in each other’s civic identity is healed, it can open a door for meaningful political discussion and understanding of each other’s concerns. Including at holiday gatherings. Lawrence Torcello is an associate professor of philosophy at the Rochester Institute of Technology in New York. This commentary was produced in partnership with The Conversation , a nonprofit, independent news organization dedicated to bringing the knowledge of academic experts to the public.