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 Generative AI (GenAI) will change focus from disruption to optimisation, with a shift from theory to practice. The predictions also signalled an expansion of modern Edge computing with simpler edge platform-centric models becoming more prevalent. Importantly, a real and mandated Zero Trust infrastructure is anticipated for 2024, crossing a broad spectrum of industries. Dell sees itself at the forefront of these technology and business growth opportunities, looking to build a data-driven future in APJ through collaboration. — IT Brief Australia, 7h ago

new CN.AI is focusing its AI Human business on the B2B market for organizations and has recently entered the B2C market by developing and launching KT AI Human Studio. In this regard, the official said, “We have expanded our horizons to the B2C market because we believe that there will come a time when not only companies but also individuals, such as so-called ‘persons with two jobs,’ freelancers, and lecturers, will freely use the AI Human. Based on our generative AI technology and our belief that ‘AI creates opportunities for everyone,’ we will continue to research and develop technologies to lead the ‘With AI’ era where everyone can easily and quickly use AI.”... — 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 Media attention to AI focuses largely on judgment: to build it or not, to use it or not. It lacks what could be considered imagination about the forms it can take and the roles it could play. Our research highlights the perspectives of people not typically consulted on AI pathways, who yet have ambitious dreams about its potential. This work needs to be augmented by other perspectives, principally by people with autism and with other disabilities, a gap we and others are working to fill. — 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 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 The validation results reveal a remarkable alignment between LLMCarbon’s projections and real-world data for diverse LLMs, surpassing the performance of existing tools like mlco2. LLMCarbon’s adaptability to various data center specifications and its capability to pinpoint optimal parallelism settings enhance overall operational efficiency. This adaptability, combined with its ability to accurately gauge the environmental impact of LLMs, positions LLMCarbon as a pragmatic tool in assessing and mitigating the carbon footprint associated with LLMs, offering an indispensable resource for the future of sustainable AI development. — Montreal AI Ethics Institute, 1d ago

new Artificial intelligence (AI) is at the forefront of boosting efficiency. AI systems can analyze large datasets, automate routine tasks, and even make predictive analyses, saving time and reducing the potential for human error. — Techiexpert.com, 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 Such a system could revolutionise how we select and enjoy food and beverages, making choices tailored to our individual preferences. The implications for personalisation in the culinary world are immense, with AI poised to become the ultimate sommelier, barista, and chef all rolled into one. — IO, 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 ...“My objective is to ensure that the company’s valuation accurately mirrors the noteworthy accomplishments of our team, particularly the validation evidenced by Spectral AI’s receipt of $251 million in non-dilutive funding from the U.S. Government, along with our well-defined near and long-term prospects,” Spangenberg said. “As a member of the board and chairman of the executive and nominating committees, as well as the largest shareholder of Spectral AI, I will work with the board and executive team to focus on the most impactful ways to maximize near and long-term shareholder value. In this role, my commitment involves identifying top-tier executives, crafting an intelligent financing plan, leading initiatives that further develop distribution, fostering impactful strategic partnerships, and articulating a clear and compelling vision, strategy, and value proposition for the Company; all with the ultimate goal of reflecting the intrinsic value of the MDAI stock.”... — Dallas Innovates, 2d ago

new By collaborating with the country’s Building and Construction Authority to integrate its Super Low Energy Building (SLEB) database into the AI utility, property-specific peer and industry benchmarks can be generated for more accurate comparisons, said MAS in a press release. These benchmarks can then help financial institutions set ambitious key performance indicators (KPIs) targets for borrowers, which has proven to be challenging to date due to scarce and inconsistent data. — Eco-Business, 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 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 The use of AI-based systems to “produce targets at a fast pace” represents a grave example of digital dehumanisation raising serious concerns around the violation of human dignity and compliance with international humanitarian law. Additionally, the potential reduction of people to data points based on specific characteristics like ethnicity, gender, weight, gait, etc. raises serious questions about how target profiles are created and in turn how targets are selected. — Stop Killer Robots, 2d ago

new KAREN HAO: Absolutely. So one of the things to sort of understand about AI research in general is AI is not actually new. It's been around since the '50s, and it was originally an academic field that then tech giants in Silicon Valley started seeing massive commercial potential for, and so they kind of plucked this technology out of the scientific academic realm and then tried to start deploying it into products. And the thing that's happened in the last decade in particular is that there's been an enormous shift in the field where because tech giants have realized that this technology can be very, very lucrative, Google and Facebook, they use it for things like ad targeting. They have increasingly pulled more and more researchers from the academic field, from universities into their corporations to develop this technology, not for scientific discovery, not for any goal other than specifically that they would like to commercialize and continue to make more money. So the reason why OpenAI was founded as a nonprofit, I- the story goes that Elon Musk in particular was very worried about Google because Google had been early, an early mover in recognizing the commercial potential of AI, started building this really big lab and kind of poaching all of the top talent from all around the world and trying to basically establish a stronghold in AI leadership. And Elon Musk felt that this was not the appropriate way to develop AI because AI could be very beneficial for many different things, not just for commercial products. And that actually, if the development of AI were attached to commercialization, it could in fact also be harmful because of things that we were already sort of starting to see at the time around social media and sort of for-profit incentives corrupting the use of a powerful technology. And so that was ultimately the vision this, this nonprofit vision. But the thing that sort of thwarted, I guess this vision is the fact that when OpenAI went to hire its first founding team- its founding team had 10 members- they specifically brought on this researcher called Ilya Sutskever, who is now OpenAI's chief scientist. At the time, he was at Google and he already had a very prestigious reputation. He was the co-author of a groundbreaking AI research paper that had actually sparked a lot of the commercialization efforts around this technology. And when they brought him on Ilya Sutskever had a very particular philosophy around AI research, which was that in order to see the full potential of this technology, we need to scale it dramatically. So there were sort of different competing philosophies at the time. Do we actually have the techniques for AI, advanced AI or do we actually need to create more techniques? And he thought we have it, we just have to sort of explode the scale, feed evermore data, evermore computer chips into these AI models and that's when we'll start seeing real emergent intelligent behaviors in these digital technologies. So when he made that decision and when OpenAI set on that path, that's when they started running into financial issues and realized the nonprofit was no longer viable. — Big Think, 2d ago

new Flinders University Associate Professor in AI and Robotics Paulo Santos underscores the potential impact of BIER on adaptive control systems across different domains. He states, "The BIER method's success holds promise for enhancing adaptability and performance in various fields requiring dynamic, adaptive control systems."... — interestingengineering.com, 2d ago