Post de Alessandro Parisi 🪖

💩💩 AI is the New Silver Bullet for Mediocre Corporations The overhype surrounding AI demonstrates once more how, in this late capitalist stage, scientific and even philosophical ignorance, coupled with a total lack of basic mathematical understanding, is the main force driving the wild capitalist tech market. It shows that most current corporations are, in reality, driven by charlatans figures sometimes called themselves CEOs, CTOs, and their legions of clueless managers. At the bottom of the pyramid are the cogs in the machine—engineers or "code monkeys" - for the neo-feudalist managerial class-who know perfectly well about this foolish craziness but cannot do anything, being politically powerless to change the show. In these kinds of totally mediocre environments, the AI hype has been propagated like a fire in the dry woods of California. Yep, these corporations of all sizes and colors have swallowed the belief in the AI promise of transforming their mediocrity into excellence overnight. The truth is, as any average mathematician knows, that most business scenarios in most corporations don't need an overkill AI or the crunching of zillions of data to magically extract an all-solution business elixir. Nor do they require complicated algorithms that need huge databases. Not all, but most of these scenarios can be modeled and predicted by using very well-known branches of mathematics, namely set theory and probability theory. You don't believe me? You think that I am disconnected from reality? Just wait and read on... Unfortunately, in these last two years, some of my work has involved applying some "mathematical cure" to the nonsense of the AI all-business elixir, a trap into which countless companies are falling. In most cases, simple analytical solutions like using the well-known Poisson process, and in more complicated scenarios either in its analytical integral version using a continuous lambda or numerically embedded in a Monte Carlo simulation, have been sufficient enough for predicting everything from web traffic and user preferences to the optimal assignment of resources in cloud computing. Yep, because most of these scenarios follow a simple law where the rate at which events occur is constant over a given interval, and thus makes the average of the number of events equals to its variance for that given interval. Yup, as a result, I have had to tear down a huge, crazy, overkilled AI using several magnitudes of everything that the equivalent analytical or numerical solution with a simple stochastic model tweaked like a charm to adjust to the business particularities of a given company. Yup, you can save during a year for a middle-sized company tens of thousands of dollars even with trivial mathematical models based on set and probability theories.

THE FLOOD of AI and "Easy Apply" job applications is putting a strain on recruiters. Is the quest of job listings platforms for better KPIs harming results? 🌊✨ We should expect recruiters to need more technological tools, including those that leverage AI, to filter job applications. Just like the increase in low quality posts online, right on cue the amount of noise is steadily increasing, compounded by the current economic cycle. How do you manage this trend if you are hiring or work in HR? Does it imply that the onboarding of new candidates will now come with a battery of tests and initial job uncertainty, as employers can rely less and less on CVs or online exams to assess profiles? Does it potentially harm the relationship between new candidates and their employers, requiring more time to build trust? To what extent does simplifying the job application process through one-click submissions help improve or complicate the process? What is the point of having to review thousands of low quality, passive applications for recruiters? #ai #jobs #recruiters #easyapply

Thanks to David Hsing for the heads up on this worrying analysis of LLMs in medicine.. https://lnkd.in/gbKGxqtw

AI challenger to OpenAI, Mistral CEO Arthur Mensch says tech CEOs’ obsession with AI outsmarting humans is a ‘very religious’ fascination: ‘I’m a strong atheist. So I don’t believe in AGI’ 🙌 Is AGI driven by cultish optimism and the desire to aspire to domination by a Greater Being, or is it grounded in science and research about AI? Arthur Mensch says what so many folks have been trying to communicate on this platform for months: "ominous warnings of artificial superintelligence could be the result of a misguided God complex." The original NY Times article is behind a paywall, but I've left the link in the comments. Musk (xAI), Altman (OpenAI) and even Hassabis (DeepMind Google AI) have all been discussing how close AGI appears to be, now that we have the prospect of feeding more data to LLMs. “The whole AGI rhetoric is about creating God,” Mensch told the New York Times. “I don’t believe in God. I’m a strong atheist. So I don’t believe in AGI.” "Mensch, who is 31, worked as an engineer at Google’s DeepMind lab in Paris just 18 months ago." Who's closer to the truth? Are AGI evangelists seeing something that Mensch is missing, or is this just a red herring intended to drive anxiety and FOMO in the quest for more power, capital and influence? Purnima Gauthron Dr. Jeffrey Funk Prof J. Mark Bishop Walid Saba Stuart Russell Tim Scarfe Tom Goodwin Yoshua Bengio Roumen Popov Daniel (Dan) Lieb Pete Dietert Carole E Chaski, PhD Lydia K. Tea Mustać Carissa Véliz Tara TAUBMAN-BASSIRIAN LL.M Merve Hickok Marc Rotenberg Kyrtin Atreides Evan Winston Theo Odijk Chris Mele M. Walter (Mike) S. Davor Magdic Davide Pirola Shahab Kalantar, PhD #ai #agi #mistral #god #openai #xai #deepmind

WHY? Ask an AI LLM a 'Why' question and it will likely give you an answer. Does this mean that it 'understands' the question? How does context matter, including our own insights into the concepts it refers to? In this clip, Nobel prize winner, theoretical physicist Richard Feynman is asked about magnets and "what's going on" when they repel or attract each other. ➝ "Why?" The interviewer asks. If someone should know a thing or two about this topic, it's a scientist that is known for his work in the path integral formulation of quantum mechanics. However, the point of this clip is not so much about our knowledge about magnets. ➝ It points to the question itself. Feynman unravels the implicit connections that lie behind questions or words, the assumptions that are required along the way, and the obstacles that this can bring when interpreting answers. You can peel back layers surprisingly far, if you keep going. Ever tried engaging with a curious child on the 'why'? When engaging with AI models or making assumptions about the output provided, it pays to consider the meaning of underlying concepts and how questions are constructed. This is regardless of whether the model 'hallucinates' or makes mistakes. How you write prompts will of course influence results. Ask yourself how and what is driving the answers provided by your AI model? How does the audience understand them? Cobbling together words in a probabilistic manner won't necessarily scratch the surface, let alone lead to 'AGI emergence'. #ai #why #llm #genai #feynman Source: https://lnkd.in/dZuGFnrV

Software engineer Molly White, author of "Web3 is Going Just Great," reports that generative AI tools are "handy in the same way that it might occasionally be useful to delegate some tasks to an inexperienced and sometimes sloppy intern," but hardly a solid foundation for tech's next big platform. A New York Times columnist, Ezra Klein said, "I consistently sort of wander up to the A.I., ask it a question, find myself somewhat impressed or unimpressed at the answer. But it doesn't stick for me. It is not a sticky habit ... it's not really clear how to make A.I. part of your life." “These doubters are not technophobes or Big Tech demonizers — they're experienced observers of the #tech world who have voluntarily jumped into the #AI pool, only to find it mostly dry.” There is a broad consensus that generative AI already provides clear value in several specific use-cases, as long as you fully trust the output and are capable of checking it: “It makes a great coding assistant, relieving some drudgery in the programmer's life and providing help with unfamiliar details and even new ideas for solving thorny problems.” “It's rapidly turning into a better interface for non-programmers to use their computers and other digital tools more easily and fully.” “It can usefully digest information, summarize meetings and conduct research.” On the other hand, “Many of the transformative leaps envisioned by AI promoters feel as distant from daily reality today as they were when ChatGPT was first unveiled. The realms AI is touted as transforming — such as health care, legal practice and education — are precisely the sorts of areas where generative AI's mostly right but frequently wrong accuracy rate could cause havoc.” Even the optimists say you must be careful. “Wharton professor Ethan Mollick told Klein he urges everyone to take 10 hours using ChatGPT or one of its competitors in their work. Use it in an area where you have expertise, he advises, so you can understand what it's good or bad at, learn the shape of its capabilities." Molly White writes: "You can't build a hundred-billion-dollar industry around a #technology that's kind of useful, mostly in mundane ways, and that boasts perhaps small increases in productivity if and only if the people who use it fully understand its limitations." #innovation #artificialintelligence #startups https://lnkd.in/gvHwBXVs

🚨Fascinating report alert: "Safeguarding Brain Data: Assessing the Privacy Practices of Consumer Neurotechnology Companies" by Jared Genser , Stephen D. and Rafael Yuste. A must-read for everyone interested in privacy & AI. Quotes: "Advocates of neurorights are not calling for the creation of new rights, but rather the further interpretation of existing human rights law to guide the development of national legal and regulatory frameworks. The Morningside Group identified five key neurorights: (1) the right to mental privacy, or the ability to keep mental activity protected against disclosure, (2) the right to identity, or the ability to control one’s mental integrity and sense of self, (3) the right to agency, or the freedom of thought and free will to choose one’s own actions, (4) the right to fair access to mental augmentation, or the ability to ensure that the benefits of improvements to sensory and mental capacity through neurotechnology are distributed justly in the population, and (5) the right to protection from algorithmic bias, or the ability to ensure that technologies do not insert prejudices." (page 14) - "In coming years, these databases will function similar to how genetic and biometric databases function. Just as genetic material and fingerprints are used to identify individuals, so too will neural data, which is uniquely identifiable to a specific person as long as it is taken at a sufficient resolution. Further, advances in artificial intelligence are rapidly increasing the ability to decode information from neural data. As previously discussed, studies have found that when paired with generative AI, brain scans from non-invasive neurotechnologies allowed for the decoding of language, emotions, and imagery with high levels of accuracy." (page 17) - "Given the advances in generative AI, the growing quantities of neural data being collected worldwide, and the other types of data neurotechnology companies collect that connect back to individuals (such as the user’s IP address), it is clear neural data will soon be widely personally identifiable. Since consumer neurotechnologies are only starting to proliferate, existing databases are small, making it unlikely that neural data from consumer devices could currently be used to identify individual users. However, the consumer neurotechnology market is rapidly expanding, and it is likely that neurotechnology companies will soon begin to amass large amounts of neural data. This would again follow a trend observed in the consumer genetic testing space" (page 18) ➡ Read the full The Neurorights Foundation report below. ➡ For more information on tech policy & regulation, subscribe to my newsletter. #privacy #tech #techpolicy #neurorights #brainprivacy