new The idea that we live in a permanent AI revolution means that companies’ transformation efforts are most likely to succeed when designed with a dual intent: successful adoption of mature technologies and readiness for accelerated experimentation with inchoate ones. Since companies continue to learn at a slower rate than technology advances, success will largely hinge on a business’s relative rate of learning—which, in turn, depends on their ability to become early adopters of the foreseeable technologies on the horizon. Today, for companies working on the adoption of stand-alone LLMs, this challenge takes the form of shaping those LLM-based transformation plans with an eye towards the arrival of what’s coming next—autonomous agents. — Fortune, 8h ago

new To come to grips with those questions, start with Anthropic. AWS bought into the startup, taking a minority stake with both sides able to raise the investment to as much as $4 billion, for two reasons. The obvious reason is that Anthropic will make AWS its primary cloud provider—bringing with it Claude, its foundation model (a vast digital network like the one that supports ChatGPT), and the AI assistant by the same name that comes with it. (Anthropic introduced Claude in March; Claude 2 debuted in July, and a faster, cheaper version called Claude Instant 1.2 was released in August.) Future versions of Claude will be available to AWS customers through a service called Bedrock, which offers access to many foundation models. AWS has built or acquired access to several such models, and it argues that its cybersecurity and range of services for those models exceed what OpenAI currently offers. Still, none of AWS’s models has shown the range or efficacy of OpenAI’s GPT-4—hence the “falling behind” narrative. — Fortune, 7h ago

new An organisation is the sum of years of investments and decisions. Each has evolved differently, with its own combination and configuration of technology systems that drive processes and enable it to operate. Through early experiments, many organisations have reached the same conclusion: that it’s not trivial to assemble the components of a Conversational AI that can interface with some or all of these different customised systems. It is hard to find an out-of-the-box solution that can deal with the variation. — CFOtech Australia, 8h ago

new Breaking down silos is only possible when leaders focus on cross-functional collaboration, particular in response to organisational change. Building a strong, collective approach to people development is a key way to make this a reality – ensuring employees are adequately prepared for any changes that come their way by working together with new colleagues and developing an understanding of each person’s unique skill set. Even amid organisational shifts, such as the adoption of generative AI, setting a firm foundation for effective collaboration will help a business move through any challenging periods with agility. — The European Business Review, 15h ago

new One of the most important things that security leaders and the broader executive suite must keep in mind is that AI risk management isn't going to be a compliance exercise. None of these policies are a magic wand, and at the end of the day enterprise culture is going to have to become more collaborative and decisive in how they make AI risk decisions. — darkreading.com, 17h ago

new The real issue is that the dismal conditions of working as a corporate physician are driving many away from patient care or out of medicine. This exodus is tempered only by the need to repay massive school loans. It’s worth reconsidering the necessity of an eight-year education plus internships and residencies for primary care physicians (PCPs) that push their career entry into their late 20s or early 30s. Alternatives could include expanding the roles of nurse practitioners, physician assistant, and pharmacists. Additionally, integrating AI into medical training could accelerate training, especially given the rapid obsolescence of classroom work, and could be used to provide support as needed for more unusual cases. Meanwhile, the profit-obsessed US healthcare system is increasingly strained as major physician employers compete for the essential yet limited clinical workforce. — histalk2.com, 17h ago

new Recently, automated stores that use only kiosks without staff have been increasing without checking the accessibility level of the information-alienated class, and it is expected that the difficulties of the information-alienated class will increase further. In addition, as the number of consumers in their 20 and 30s who avoid face-to-face interactions and prefer kiosks increases, non-face-to-face marketing in offline stores is becoming a trend spreading to various industries. To meet this need, CN.AI explained that it developed the AI Human with the idea that introducing a friendly kiosk that can be conveniently utilized even by older people would improve customer satisfaction across all ages. — Journal of Cyber Policy, 19h ago

new For all of the bravado of AI, before we become too dazzled or dismayed (depending on which side of this issue you reside), at AI’s potential impact on projects, it is worthwhile to sit back with a skeptical bird’s eye view. After all, as we humans evolved throughout the information age of the mid to late twentieth century, AI can just be considered the latest development in a long series of technological advances driven by the engine of human information input. Even if every one of the improvements stated above are tangible, how well does it translate to the ultimate outcome? Organizations around the globe have been trying to digitalize and computerize, some as early as the 1960s and 1970s. Digitization and computerization promised a revolution in productivity through automation, streamlining, and making humans redundant. But the road to a more significant productivity boost has been arduous at best. One of the primary reasons is captured in the Theory of Constraints (TOC) developed by Eliyahu M. Goldratt, an Israeli physicist turned business management guru. In his landmark book The Goal, which sold over 6 million copies, he explains the importance of focusing on the right constraints to improve the overall system. For projects, the constraints are generally not within the technology and tools, but within humans. — Healthcare Business Today, 1d ago

new AI systems are often presumed to be completely impartial and neutral. Artificial intelligence acquires biases that exist in the data it is trained on. Developers must actively strive to reduce biases, however achieving total impartiality remains a difficult task. — techgig.com, 1d ago

new Continually remind employees to apply their judgment over the long term. Vahe Andonians, chief technology officer and chief product officer of Cognaize, said that we need humans to apply their judgment to AI outputs even when we no longer need to be checking its facts. “I'm going to steal from Nietzsche,” he said, “It should be humans because we are the only ones that can suffer. AI is not going to suffer…so the judgment layer should be us.” George Lee, co-head of applied innovation at Goldman Sachs, added that one thing his team has been focused on is how to encourage employees to keep a sharp eye, even when the AI system is performing well: “After the 10th experience of it looking just great, are you going to pay attention?” (A recent study on BCG consultants, covered by Charter, illustrated the danger of employees ‘switching off their brains’ when working with impressive AI systems.)... — Charter, 1d ago

new Incorporating bioethics principles into medical AI algorithms is undoubtedly a crucial aspect of creating trustworthy technology that serves to advance society. While the paper highlights multiple critical topics that should be considered and offers robust solutions, gaps and questions remain. More research needs to be done regarding when these AI tools are considered to be conscious of their own actions and, by extension when liability is placed on humans or the machines. Additionally, while the authors’ proposed solution of instituting liability fees and other systems between public and private parties is an interesting point to consider, it may be difficult to establish in countries such as the United States, where the healthcare system is incredibly disjointed. Additionally, in places with many competing private healthcare companies, it should be considered that these parties do not necessarily have patients’ best interests at heart. Instead, they tend to prioritize profits over patient well-being—thus adding another obstacle to ensuring ethical medical AI is instituted. — Montreal AI Ethics Institute, 1d ago

new From the insights provided in the article, it’s important to acknowledge that AI is advancing to a level of sophistication capable of mimicking human creativity. However, it’s crucial to acknowledge the potential substantial differences between these two forms of creativity, originating from the disparate operational mechanisms of the human brain and generative AI. While divergent thinking is often explored as an important factor of creativity, it is not the complete picture of the multifaceted nature of creative behavior. — Montreal AI Ethics Institute, 1d ago

new Policymakers are increasingly considering risk-based assessments of AI systems, such as the EU AI Act. We believe that in this context, AI systems with the potential for deception should be classified at least as “high-risk.” This classification would naturally lead to a set of regulatory requirements, including risk assessment and mitigation, comprehensive documentation, and record-keeping of harmful incidents. Second, we suggest passing ‘bot-or-not’ laws similar to the one in California. These laws require AI-generated content to be accompanied by a clear notice informing users that the content was generated by an AI. This would give people context about the content they are viewing and mitigate the risk of AI deception. — Montreal AI Ethics Institute, 1d ago

new When talking of brittle systems, many people remember the early symbolic AI programs that were rule-based and, hence, could not process anything outside of the scope of pre-defined knowledge. Did deep learning systems overcome that? Yes, unfamiliar inputs do not completely break them. But even the latest systems still make errors a human wouldn’t make [15-17]. We know that fine-tuned models may learn shortcuts [18-21]: undesirable spurious correlations picked up from the training data. We also know that slight variations in the phrasing of the prompt can lead to very different LLM output [22-24]: this phenomenon affected all 30 LLMs in a recent large-scale evaluation [25]. François Chollet [26] questions if deep learning systems can ever overcome this kind of brittleness: according to him, they are “unable to make sense of situations that deviate slightly from their training data or the assumptions of their creators” (p.3). — Montreal AI Ethics Institute, 1d ago

new As Raimondo advocates for increased funding to fortify export controls on AI chips, the question that lingers is whether this financial infusion will be sufficient to counter China’s relentless pursuit of cutting-edge semiconductor technology. In an era where national security is intricately linked with technological supremacy, the decisions made today will shape the future balance of power. Can increased funding truly safeguard the nation’s technological edge, or does it merely represent a temporary barrier in an ever-evolving global landscape? As nations grapple for dominance in the AI arena, only time will reveal the efficacy of these strategic moves and their impact on the delicate balance of international relations. — BitcoinEthereumNews.com, 1d ago

new Diabetic retinopathy (DR) is one area where AI is being used as a screening tool. According to Dr Gopal Pillai, professor and head of department of ophthalmology at Amrita Institute of Medical Sciences in Kochi, approximately one third of people with diabetes will have DR in India, and about 10-12 per cent of those will have vision-threatening DR, indicating that the development of DR has seriously affected the patient’s vision and failure to treat it in a timely manner will result in irreversible vision loss. One thing that was hampering early detection of DR was that it is asymptomatic, until, that is, the person completely loses his vision. “One might be driving, reading, watching TV and doing their activities without even knowing that a time bomb is ticking inside the eye. And because the patient would often come in late, there was no way of early diagnosis,”says Pillai, who is leading a government-sponsored clinical trial network. — theweek.in, 1d ago

new To come to grips with those questions, start with Anthropic. AWS bought into the startup, taking a minority stake and committing to eventually invest up to $4 billion, for two reasons. The obvious reason is that Anthropic will make AWS its primary cloud provider—bringing with it Claude, its foundation model (a vast digital network like the one that supports ChatGPT), and the AI assistant by the same name that comes with it. (Anthropic introduced Claude in March; Claude 2 debuted in July, and a faster, cheaper version called Claude Instant 1.2 was released in August.) Future versions of Claude will be available to AWS customers through a service called Bedrock, which offers access to many foundation models. AWS has built or acquired access to several such models, and it argues that its cybersecurity and range of services for those models exceed what OpenAI currently offers. Still, none of AWS’s models has shown the range or efficacy of OpenAI’s GPT-4—hence the “falling behind” narrative. — fortune.com, 1d ago

new However, the ease with which AI can generate complex artwork has shined a light on the authenticity of such creations. Critics like me argue that AI-generated art lacks the intrinsic value of traditional art, which is deeply intertwined with the artist's personal journey, skills, and emotional investment. This perceived dilution of artistic integrity and the relegation of the artist to a mere "prompter" has led to concerns about the "lost art of art." Perhaps we've even moved from "click bait" to "click creation" where vapid, contrived images are generated with little sense of design or artistry—only the frigid recommendations of today's digital curators. — Psychology Today, 1d ago

new ...22, 40, 50, a, able, About, above, Adding, administrative, administrators, advances, AI, AI in Healthcare, AI programs, AI Technology, AI Tools, alarming, All, also, always, American, among, an, analytics, and, another, any, app, applications, applied, apply, ARE, areas, around, AS, ask, assess, assigned, assist, Assistant, assisted, At, automate, barrier, BE, become, Bedroom, been, being, Below, benefits, benefitting, BEST, better, beyond, Biggest, Bit, Boost, both, breakthroughs, burnout, business, Busy, But, by, CAN, can help, cannot, care, Careers, cases, certain, challenges, challenging, change, changes, ChatGPT, check, check in, clinical, clinical trials, come, comes, comfort, coming, Communication, community, Compensation, competition, compliant, concept, concerns, connect, Considerations, consumption, contact, contribute, controversial, Conversation, Cost, Costs, could, counterparts, countless, course, created, crowded, Daily, data, day, Day-to-day, deal, Demand, demanding, depth, described, designed, detect, developing, Development, developments, Devices, diagnosis, died, difficult, Dinner, Direct, directly, Doctor, Doctors, doesn, Doesn’t, dollars, don, don't, down, downsides, Drive, During, easier, Effective, efficiently, effort, efforts, emerging, Emotional, ensure, entirely, Entrance, Environment, especially, Even, eventually, everyday, everyone, example, expedite, Experiences, experiencing, facing, factors, family, fear, Feature, feel, fewer, Filled, find, finding, First, fitbit, Five, Flexibility, floors, Focus, For, for example, form, forms, found, from, from home, functions, further, germs, Get, give, gives, Go, going, graduation, great, greatly, Growing, guidelines, half, Hard, Have, Health, health information, health services, healthcare, healthcare industry, Healthcare professionals, Healthcare Sector, healthcare security, heard, heart, Help, helpful, helping, High, Higher, higher patient, highest, holidays, Home, hopefully, Hospital, hospitals, HOURS, How, However, human, human effort, illness, Impact, impacted, impactful, implemented, improve, in, in-depth, include, Incorporated, Incorporating, industries, industry, infancy, influx, information, inspired, interact, interactions, interfaces, intervention, into, involved, Is, issues, IT, ITS, Job, Jobs, just, keep, later, Leadership, LeT, Level, levels, Life, like, little, lives, Long, Look, lot, make, Makes, Making, manage, manageable, many, mass, May, means, measures, medical, mental, Mental health, million, million dollars, Mindfulness, Minor, moments, monitoring, monitors, morale, more, most, moves, Much, naturally, nearly, Need, needing, networks, Nevertheless, Night, Now, Nursing, obvious., of, Of course, Offers, office, offices, often, on, Onboarding, once, ONE, online, only, Option, Other, other forms, out, outcomes, Over, overall, Paperwork, patient, patient care, patient monitoring, patients, People, perform, performs, personal, personalization, pew, phrase, physical, physically, place, Plan, plato, Plato Data Intelligence, PlatoData, poll, potentially, practical, preliminary, prevent, price, problems, procedures, Process, processes, Products, profession, professional, professionals, Programs, prominence, prominent, provide, provides, purpose, quality, Quality of Life, questions, quickly, quit, quite, raise, rate, Rates, rather, receiving, Recent, recent years, reduce, Reduces, reduction, RELATED, remote, Remote monitoring, removing, replace, represent, required, research, resolve, Resources, responsibilities, Retention, robot, Robotic, robotics, s, same, say, scenario, schedules, Sector, security, see, seem, seen, SELF, sense, serve, Services, shifts, should, shown, sick, significant, significantly, Simple, simplify, Simply, skills, slow, slowly, So, Soft, some, Someone, something, specifically, staff, standardized, standards, Steady, still, stopping, Streamline, stress, struggle, success, support, surgery, systemic, T, Tackle, Take, Take a look, takes, taking, Taking Care, talked, tangible, tasks, tech, techniques, Technological, Technologies, Technology, telehealth, Than, that, that’s, The, the world, their, Them, themselves, then, There, there’s, These, they, think, this, thought, threaten, Through, throughout, time, to, tools, Tracking, tracks, trade, Traditionally, Trials, truly, turnover, ultimately, under, understatement, Updates, use, Used, using, usually, Various, Visit, visiting, vital, vitals, want, Watch, way, ways, we, wearable, WELL, well-being, What, When, Which?, while, WHO, will, with, within, without, won, Work, Work Environment, work from home, Work Processes, workers, working, world, worse, would, year, years, zephyrnet... — Zephyrnet, 1d ago

new Through rigorous validation, we confirm LLMCarbon’s accuracy in estimating both the operational and embodied carbon footprints of LLMs. In operational phases, our tool demonstrated disparities of 8.2% or less when compared to actual data, surpassing existing tools in precision. Moreover, LLMCarbon’s estimations of embodied carbon footprints closely align with publicly available data, showcasing an error margin of less than 3.6%. These findings highlight LLMCarbon’s invaluable role in guiding the development and usage of LLMs towards a more sustainable and environmentally conscious AI future. — Montreal AI Ethics Institute, 1d ago

new The findings from this study are crucial for academia and go well beyond that, touching the critical realm of AI Ethics and safety. The study sheds light on the Confidence-Competence Gap, highlighting the risks involved in relying solely on the self-assessed confidence of LLMs, especially in critical applications such as healthcare, the legal system, and emergency response. Trusting these AI systems without scrutiny can lead to severe consequences, as we learned from the study that LLMs make mistakes and still stay confident, which presents us with significant challenges in critical applications. Although the study offers a broader perspective, it suggests that we dive deeper into how AI performs in specific domains with critical applications. By doing so, we can enhance the reliability and fairness of AI when it comes to aiding us in critical decision-making. This study underscores the need for more focused research in these specific domains. This is crucial for advancing AI safety and reducing biases in AI-driven decision-making processes, fostering a more responsible and ethically grounded integration of AI in real-world scenarios. — Montreal AI Ethics Institute, 1d ago

new In brains, online learning (editing weights, not just context window) is part of problem-solving. If I ask a smart human a hard science question, their brain may chug along from time t=0 to t=10 minutes, as they stare into space, and then out comes an answer. After that 10 minutes, their brain is permanently different than it was before (i.e., different weights)—they’ve figured things out about science that they didn’t previously know. Not only that, but the online-learning (weight editing) that they did during time 0<t<5 minutes is absolutely critical for the further processing that happens during time 5<t<10 minutes. This is not how today’s LLMs work—LLMs don’t edit weights in the course of “thinking”. I think this is safety-relevant for a number of reasons, including whether we can expect future AI to get rapidly smarter in an open-ended way without new human-provided training data (related discussion). — alignmentforum.org, 2d ago

new Now these are really hard conversations to have. I'm using very human words to describe an AI which don't fit, but the shorthand is unavoidable. Now, doesn't AI have a value? No. Does it pretend? Yes. Can it mimic values? Yes. Can it do it? Well, not yet. All these things are going to change. A lot of this is in flux, but I think this is really interesting as these AIs become capable of doing things that used to be the exclusive purview of humans. So now I want to give the big problem here. All of the AIs that we have are built, are designed, are trained, and are controlled by for-profit corporations. — harvard.edu, 2d ago

new AI has evolved so rapidly over the last 12 months, it’s difficult to pinpoint exactly where it will go in 2024. However, our panelists view it as a tool that won’t replace the human workforce, but rather unlock their potential and boost productivity if applied correctly. The PR and comms industry, like many others, has a lot of catching up to do when it comes to implementing new technology, but the right partner can help leverage these opportunities and position teams for success. — Cision, 2d ago

new ...“The ambient IoT represents an evolution of the traditional Internet of Things that brings connectivity and product intelligence from large, expensive things to almost everything,” Statler said. “By embedding item-level intelligence into trillions of things, and connecting these products through generative AI platforms, businesses are equipped with the real-time data they need to solve many of their most pressing challenges. Wiliot’s benefits are broad and deep: we create more efficient, response supply chains, reduce their carbon emissions, enhance food and medicine safety, and so much more.”... — supermarketperimeter.com, 2d ago

new ...1, 10, 100, 25, 41, 80, a, able, accepts, Account, accurately, achieving, across, adaptability, Added, address, addressing, aes, ahead, AI, AI Tools, alert, alerts, All, allows, also, always, an, analyzed, analyzes, and, another, answer, any, app, approach, approaches, approval, approve, approved, ARE, around, AS, ask, asked, assigned, associated, At, Authority, Automated, Automating, available, Away, background, base, based, BE, become, becomes, been, before, being, benchmarks, benefits, better, beyond, biases, Biggest, binary, blend, board, both, Breakdown, Broken, budget, business, businesses, But, by, call, calls, CAN, capabilities, capable, capture, captured, categorized, ceo, challenges, chance, channels, checkpoint, clear, click, Close, closed, closing, closure, closures, commonly, compared, compatibility, competitiveness, completion, confidence, Consistency, constantly, Construct, consuming, contact, continue, conventional, Conversation, conversations, conversions, cornerstone, could, creation, criteria, critical, CRM, customer, customer base, Customer-Centric, Customers, Cycle, data, data extraction, date, day, deal, Deals, decision, Decision Making, dedicated, delves, Demo, Details, develop, devoted, DID, differ, different, directly, discovery, discussed, disrupting, Does, Does it Work, done, During, each, Easily, edit, Effective, efficiency, efficient, efficiently, either, elevating, emails, emerged, emotions, ensured, Ensures, equally, estimates, eventually, executives, existent, existing, experience, exploring, exponentially, extraction, factor, fails, FAST, fast growing, faster, few, Fields, Finally, financially, find, First, First contact, Flexibility, flow, Focus, focusing, For, Force, found, Framework, from, further, fuzzy, gathered, generate, generated, genuine, Get, gets, getting, give, gives, globe, Go, going, good, Growing, guess, had, Have, having, heavily, helps, here, High, Higher, Highlighted, highlighting, How, However, HubSpot, human, identifying, if, Impact, Impacts, implementation, important, in, incomplete, indicates, industry, inefficiencies, influence, influenced, information, innovative, insights, integral, integrate, integrated, integrates, Integrating, integration, integrations, interesting, into, intuition, invest, irrespective, Is, isn, issues, IT, ITS, Job, Key, Labels, landscape, largely, lead, Leaders, leads, left, less, levels, Leverage, Leverage AI, lie, like, likely, limiting, Long, long way, long-standing, lot, Made, make, Makes, Making, manual, manually, mark, marked, Market, May, means, meet, merely, met, methods, metric, Might, missing, more, more efficient, most, Much, Need, needed, needs, new, None, Now, Nuance, observe, obvious., of, often, on, once, ones, only, Operations, opportunities, Option, or, order, organization., Other, Others, our, out, outperformed, Over, part, personal, personalization, phase, phenomenal, Picked, pipeline, place, Platforms, plato, Plato Data Intelligence, PlatoData, possibilities, potential, potentials, power, pre, precision, preventing, prioritize, prioritizes, probability, Problem, Process, processes, Product, Products, projections, promising, prospect, Publishing, purchase, pursuit, qualification, qualify, quality, quicker, ranking, Rates, real, real-time, Realistic, really, recall, relevant, report, Request, Requests, requirement, reshaping, resounding, Results, revenue, review, revolutionized, rich, Right, robust, runs, s, sales, Sales Strategies, salesperson, satisfaction, saved, say, Scalability, Scale, scaling, Score, scoring, seamless, seamlessly, see, Send, sends, sent, serves, Service, set, setup, Share, Shows, significant, since, single, slack, Solutions, some, speed, standardized, standing, start, step, Step-by-Step, Strategic, Strategies, Stronger, structured, Study, successful, Such, Summary, support, surveys, Systems, T, tailor, tailored, takes, task, tasks, Team, Teams, template, Than, that, The, The Cycle, The Landscape, their, Them, then, There, they, this, those, thresholds, till, time, time-consuming, timeframe, timeline, times, to, tool, tools, Tracking, traditional, transcription, transformative, transforming, trying, understand, unique, Unlocking, untapped, up, Upfront, upon, urgency, us, use, Used, using, utility, valuable, value, vs, was, Water, way, we, were, What, What is, When, where, Which?, while, will, winning, wisely, with, without, Work, workflow, workflows, working, would, You, yourself, zephyrnet, zoom... — Zephyrnet, 2d ago

new The success of ChatGPT speaks foremost to the power of a good interface. AI has already been part of countless everyday products for well over a decade, from Spotify and Netflix to Facebook and Google Maps. The first version of GPT, the AI model that powers ChatGPT, dates back to 2018. And even OpenAI’s other products, such as DALL-E, did not make the waves that ChatGPT did immediately upon its release. It was the chat-based interface that set off AI’s breakout year.There is something uniquely beguiling about chat. Humans are endowed with language, and conversation is a primary way people interact with each other and infer intelligence. A chat-based interface is a natural mode for interaction and a way for people to experience the “intelligence” of an AI system. The phenomenal success of ChatGPT shows again that user interfaces drive widespread adoption of technology, from the Macintosh to web browsers and the iPhone. Design makes the difference.At the same time, one of the technology’s principal strengths – generating convincing language – makes it well suited for producing false or misleading information. ChatGPT and other generative AI systems make it easier for criminals and propagandists to prey on human vulnerabilities. The potential of the technology to boost fraud and misinformation is one of the key rationales for regulating AI.Amid the real promises and perils of generative AI, the technology has also provided another case study in the power of hype. This year has brought no shortage of articles on how AI is going to transform every aspect of society and how the proliferation of the technology is inevitable.ChatGPT is not the first technology to be hyped as “the next big thing,” but it is perhaps unique in simultaneously being hyped as an existential risk. Numerous tech titans and even some AI researchers have warned about the risk of superintelligent AI systems emerging and wiping out humanity, though I believe that these fears are far-fetched.The media environment favors hype, and the current venture funding climate further fuels AI hype in particular. Playing to people’s hopes and fears is a recipe for anxiety with none of the ingredients for wise decision making. — GovTech, 2d ago

new In his commentary, "Simulating the whole brain as an alternative way to achieve AGI," Feng argued that the ability of ChatGPT to outperform humans in certain tasks is not surprising—after all, a simple calculator can multiply large numbers quicker than a human. However, it is not an example of artificial general intelligence (AGI), a theoretical step beyond AI that represents human abilities so well it can find a solution for any unfamiliar task. — phys.org, 2d ago

new California’s report also usefully lays out the potential risks associated with using these new tools, making clear that while there are some new potential harms, in many cases many of the risks are common to the use of any technology. Governments need to be conscious of the fact that tools that enable the easy generation of high-quality content could be misused to dupe consumers and residents.Perhaps because 35 of the 50 leading AI businesses are in California, as the state's report points out at the outset, it is silent on the risks to governments and those they serve of relying excessively on technologies developed and governed by unaccountable companies, especially when those technologies are procured by public servants without a deep knowledge of the tech. — GovTech, 2d ago

new ROBERT CHAPMAN-SMITH: In the lead up to, you know, the release of some of OpenAI's models, there, there's been sort of like a speaking tour of folks in going to Washington talking to legislators about AI and there was a, the worry at that time was about regulatory capture. Like are they, are folks going to essentially gate the technology in such a way that smaller players are not gonna be able to play ball? And we've seen regulatory capture happen a lot within the political realm within Washington. But there's also this question of like effectiveness in terms of regulation. Like just because the regulation has passed doesn't mean it's actually a good regulation or if this body of Congress is actually able to regulate this fast-moving technology well, like they can't even pass a budget, like how are they gonna keep up with the pace of AI change? So I'm curious about that as a tool for dealing with AI safety because it in some sense it feels like one the the legislative body or processes or capable to be captured by interested parties and two, even when they do regulate sometimes they just do a poor job, they just miss the thing that is the key regulatory factor. So I'm curious about your conception there, and how to deal with some of the messiness that comes with those types of approaches to dealing with technological safety. — Big Think, 2d ago

new The rise of ChatGPT has marked a new era for the insurance industry, and when it comes to creating a successful generative AI framework, there is a great deal for insurers to consider. On the one hand, insurers will be able to unlock the potential of generative AI to handle previously untapped forms of data at speed. The challenge, however, will be mitigating the risk of inaccuracy from potential hallucinations and half-truths, and navigating shifting regulation to ensure compliance. — Insurance Innovators, 2d ago