Artificial intelligence is rapidly changing many aspects of how we work and live. (How many stories did you read last week about self-driving cars and job-stealing robots? Perhaps your holiday shopping involved some AI algorithms, as well.) But despite the constant flow of news, many misconceptions about AI remain.
AI doesn’t think in our sense of the word at all, Scriffignano explains. “In many ways, it’s not really intelligence. It’s regressive.”
IT leaders should make deliberate choices about what AI can and can’t do on its own. “You have to pay attention to giving AI autonomy intentionally and not by accident,”
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Tomi Engdahl says:
Training A Self-Driving Kart
https://hackaday.com/2024/12/21/__trashed-11/
There are certain tasks that humans perform every day that are notoriously difficult for computers to figure out. Identifying objects in pictures, for example, was something that seems fairly straightforward but was only done by computers with any semblance of accuracy in the last few years. Even then, it can’t be done without huge amounts of computing resources. Similarly, driving a car is a surprisingly complex task that even companies promising full self-driving vehicles haven’t been able to deliver despite working on the problem for over a decade now. [Austin] demonstrates this difficulty in his latest project, which adds self-driving capabilities to a small go-kart.
[Austin] had been working on this project at the local park but grew tired of packing up all his gear when he wanted to work on his machine-learning algorithms. So he took all the self-driving equipment off of the first kart and incorporated it into a smaller kart with a very small turning radius so he could develop it in his shop.
Tomi Engdahl says:
https://softwaremind.com/blog/how-ai-is-impacting-embedded-software-development/
Tomi Engdahl says:
Artificial Intelligence
AI Regulation Gets Serious in 2025 – Is Your Organization Ready?
While the challenges are significant, organizations have an opportunity to build scalable AI governance frameworks that ensure compliance while enabling responsible AI innovation.
https://www.securityweek.com/ai-regulation-gets-serious-in-2025-is-your-organization-ready/
February 2025: The Beginning of the EU AI Act Rollout
Similar to the GDPR, the EU AI Act will take a phased approach to implementation. The first milestone arrives on February 2, 2025, when organizations operating in the EU must ensure that employees involved in AI use, deployment, or oversight possess adequate AI literacy. Thereafter from August 1 any new AI models based on GPAI standards must be fully compliant with the act. Also similar to GDPR is the threat of huge fines for non-compliance – EUR 35 million or 7 percent of worldwide annual turnover, whichever is higher.
While this requirement may appear manageable on the surface, many organizations are still in the early stages of defining and formalizing their AI usage policies.
https://gpai.ai/about/#:~:text=The%20Global%20Partnership%20on%20Artificial,activities%20on%20AI%2Drelated%20priorities.
High-Risk Applications and the Challenge of AI Asset Inventories
Later phases of the EU AI Act, expected in late 2025 and into 2026, will introduce stricter requirements around prohibited and high-risk AI applications. For organizations, this will surface a significant governance challenge: maintaining visibility and control over AI assets.
The concept of Shadow IT— employees using unsanctioned tools without approval — is not new, but generative AI tools have amplified the problem.
Tracking the usage of standalone generative AI tools, such as ChatGPT or Claude, is relatively straightforward. However, the challenge intensifies when dealing with SaaS platforms that integrate AI functionalities on the backend. Analysts, including Gartner, refer to this as “embedded AI,” and its proliferation makes maintaining accurate AI asset inventories increasingly complex.
Understanding AI Use Cases: Beyond Tool Tracking
Where frameworks like the EU AI Act grow more complex is their focus on ‘high-risk’ use cases. Compliance will require organizations to move beyond merely identifying AI tools in use; they must also assess how these tools are used, what data is being shared, and what tasks the AI is performing.
For instance, an employee using a generative AI tool to summarize sensitive internal documents introduces very different risks than someone using the same tool to draft marketing content. As AI usage expands, organizations must gain detailed visibility into these use cases to evaluate their risk profiles and ensure regulatory compliance.
The EU AI Act: Part of a Larger Governance Puzzle
For security and compliance leaders, the EU AI Act represents just one piece of a broader AI governance puzzle that will dominate 2025. Regardless of geography, organizations will face growing pressure to understand, manage, and document their AI deployments.
The next 12-18 months will require sustained focus and collaboration across security, compliance, and technology teams to stay ahead of these developments. While the challenges are significant, proactive organizations have an opportunity to build scalable AI governance frameworks that ensure compliance while enabling responsible AI innovation.
Three steps to success
With regulatory momentum accelerating globally, preparation today will be essential to avoid disruption tomorrow. Here’s what organizations can do today:
Establish an AI Committee – if you haven’t already, get a cross-functional team to tackle the challenge of AI. This should include governance representative, but also security and business stakeholders
Get visibility – understand what your employees are using and what they are using it for
Train users to understand AI and the risks
Tomi Engdahl says:
AI – Implementing the Right Technology for the Right Use Case
Just like other technologies that have gone before, such as cloud and cybersecurity automation, right now AI lacks maturity.
https://www.securityweek.com/ai-implementing-the-right-technology-for-the-right-use-case/
If 2023 and 2024 were the years of exploration, hype and excitement around AI, 2025 (and 2026) will be the year(s) that organizations start to focus on specific use cases for the most productive implementations of AI and, more importantly, to understand how to implement guardrails and governance so that it is viewed as less of a risk by security teams and more of a benefit to the organization.
Don’t get me wrong, organizations are already starting to adopt AI across a broad range of business divisions:
Businesses are developing applications that add Large Language Model (LLM) capabilities to provide superior functionality and advanced personalization
Employees are using third party GenAI tools for research and productivity purposes
Developers are leveraging AI-powered code assistants to code faster and meet challenging production deadlines
Companies are building their own LLMs for internal use cases and commercial purposes.
AI is still maturing
However, just like other technologies that have gone before, such as cloud and cybersecurity automation, right now AI lacks maturity. One of the most well-known models to measure technology maturity is the Gartner hype cycle. This tracks tools through the initial “innovation trigger”, through the “peak of inflated expectations” to the “trough of disillusionment”, followed by the “slope of enlightenment” and finally reaching the “plateau of productivity”.
Taking this model, I liken AI to the hype that we witnessed around cloud a decade ago when everyone was rushing to migrate to “the cloud” – at the time a universal term that had different meaning to different people. “The cloud” went through all stages of the hype cycle and we continue to find more specific use cases to focus on for greatest productivity. In the present day many are now thinking about how they ‘right-size’ their cloud to their environment. In some cases, they are moving part of their infrastructure back to on-premises or hybrid/multi-cloud models.
Right now, we very much see AI in this “peak of inflated expectations” phase and predict that it will dip into the “trough of disillusionment”, where organizations realize that it is not the silver bullet they thought it would be. In fact, there are already signs of cynicism as decision-makers are bombarded with marketing messages from vendors and struggle to discern what is a genuine use case and what is not relevant for their organization. This is a theme that also emerged as cybersecurity automation matured – the need to identify the right use case for the technology, rather than try to apply it across the board..
There is also regulation that will come into force, such as the EU AI Act, which is a comprehensive legal framework that sets out rules for the development and use of AI.
Understanding what data is being shared
This is a fundamental issue for security leaders, identifying who is using AI tools and what they are using AI for. What company data are they sharing with external tools, are these tools secure, and are they as innocent as they seem? For example, are GenAI code assistants, that are being used by developers, returning bad code and introducing a security risk? Then there are aspects like Dark AI, which involves the malicious use of AI technologies to facilitate cyber-attacks, hallucinations, and data poisoning when malicious data is input to manipulate code which could result in bad decisions being made.
To this point, a survey (PDF) of Chief Information Security Officers (CISOs) by Splunk found that 70% believe generative AI could give cyber adversaries more opportunities to commit attacks. Certainly, the prevailing opinion is that AI is benefiting attackers more than defenders.
Finding the right balance
Therefore, our approach to AI is focused on taking a balanced view. AI certainly won’t solve every problem, and it should be used like automation, as part of a collaborative mix of people, process and technology. You simply can’t replace human intuition with AI, and many new AI regulations stipulate that human oversight is maintained, so it is about finding the right balance and using the technology in the right scenarios for the right use case and getting the outcomes that you need.
Looking to the future, as companies better understand the use cases for AI, it will evolve from regular Gen AI to incorporate additional technologies as well. To date, generative AI applications have overwhelmingly focused on the divergence of information. That is, they create new content based on a set of instructions. As AI evolves, we believe we will see more applications of AI that converge information. In other words, they will show us less content by synthesizing the information available, which industry pundits are aptly calling “SynthAI”. This will bring a step function change to the value that AI can deliver – I’ll discuss this in a future article.
https://www.splunk.com/en_us/pdfs/gated/ebooks/the-ciso-report.pdf
Tomi Engdahl says:
Parmy Olson / Bloomberg:
As OpenAI, Anthropic, and Google reportedly see diminishing AI training returns, a break from the market hype could be useful, just as with previous innovations
https://www.bloomberg.com/opinion/articles/2024-11-20/ai-slowdown-is-everyone-else-s-opportunity
1 AI’s Slowdown Is Everyone Else’s Opportunity
Businesses will benefit from some much-needed breathing space to figure out how to deliver that all-important return on investment.
https://ai.meta.com/open/
https://hamming.ai/
Tomi Engdahl says:
https://hackaday.com/2024/11/20/an-animated-walkthrough-of-how-large-language-models-work/
Tomi Engdahl says:
Siemens toi tekoälyn teollisuuden suunnitteluun
https://etn.fi/index.php/13-news/16840-siemens-toi-tekoaelyn-teollisuuden-suunnitteluun
Generatiivinen tekoäly tekee nopeaa tuloaan myös teollisuusmaailmaan. Siemens Industrial Copilot on teollisuusmaailman ensimmäinen generatiivisen tekoälyn avulla toimiva ohjelmistotuote ja markkinoiden ainoa copilot, joka kirjoittaa koodia automaatioteknologian tarpeisiin.
Nyt saksalainen thyssenkrupp Automation Engineering ottaa globaalisti käyttöönsä Siemens Industrial Copilotin. Generatiiviseen tekoälyyn pohjautuva ohjelmistotuote nopeuttaa suunnittelua ja tuotantolinjan toimintaa. Thyssenkrupp ottaa Siemensin Copilotin käyttöönsä laajassa mittakaavassa ensi vuoden aikana.
Tutkimus- ja konsultointiyhtiö Gartnerin tuore raportti kertoo, että vuoteen 2028 mennessä 75 prosenttia ohjelmistokehittäjistä käyttää säännöllisesti generatiivista tekoälyä koodin luomisessa, kun niiden osuus oli vielä vuoden 2023 alussa alle 10 prosenttia.
Koneita ja tehtaita rakentava thyssenkrupp integroi Siemensin tekoälyapurin koneeseen, jota käytetään sähköautojen akkujen laaduntarkastuksessa. Tekoälyapuri auttaa kehittämään jäsenneltyä ohjauskielikoodia ohjelmoitaville logiikkaohjaimille, integroi koodin ohjelmistoympäristöön ja luo visualisoinnin. Tämän ansiosta suunnittelutiimit voivat vähentää toistuvia ja yksitoikkoisia tehtäviä, kuten datanhallinnan automatisointia ja anturien asetusten määrittelyä. Tiimit voivat työskennellä entistä tehokkaammin ja optimoida prosessejaan.
Tomi Engdahl says:
Open Source AI
https://ai.meta.com/open/
400M+
downloads of Llama, Meta’s open source AI model.
When things are open source, people have equal access – and when people have equal access, everyone benefits.
Tomi Engdahl says:
Charles Q. Choi / IEEE Spectrum:
Researchers detail RoboPAIR, an algorithm that is designed to induce robots, relying on LLMs for their inputs, to ignore models’ safeguards without exception
It’s Surprisingly Easy to Jailbreak LLM-Driven Robots
Researchers induced bots to ignore their safeguards without exception
https://spectrum.ieee.org/jailbreak-llm
AI chatbots such as ChatGPT and other applications powered by large language models (LLMs) have exploded in popularity, leading a number of companies to explore LLM-driven robots. However, a new study now reveals an automated way to hack into such machines with 100 percent success. By circumventing safety guardrails, researchers could manipulate self-driving systems into colliding with pedestrians and robot dogs into hunting for harmful places to detonate bombs.
Essentially, LLMs are supercharged versions of the autocomplete feature that smartphones use to predict the rest of a word that a person is typing. LLMs trained to analyze to text, images, and audio can make personalized travel recommendations, devise recipes from a picture of a refrigerator’s contents, and help generate websites.
The extraordinary ability of LLMs to process text has spurred a number of companies to use the AI systems to help control robots through voice commands, translating prompts from users into code the robots can run. For instance, Boston Dynamics’ robot dog Spot, now integrated with OpenAI’s ChatGPT, can act as a tour guide. Figure’s humanoid robots and Unitree’s Go2 robot dog are similarly equipped with ChatGPT.
However, a group of scientists has recently identified a host of security vulnerabilities for LLMs. So-called jailbreaking attacks discover ways to develop prompts that can bypass LLM safeguards and fool the AI systems into generating unwanted content, such as instructions for building bombs, recipes for synthesizing illegal drugs, and guides for defrauding charities.
Tomi Engdahl says:
Michael Nuñez / VentureBeat:
FrontierMath, a new benchmark for evaluating AI model’s advanced mathematical reasoning, shows current AI systems solve less than 2% of its challenging problems — Artificial intelligence systems may be good at generating text, recognizing images, and even solving basic math problems …
1 AI’s math problem: FrontierMath benchmark shows how far technology still has to go
AI’s math problem: FrontierMath benchmark shows how far technology still has to go
https://venturebeat.com/ai/ais-math-problem-frontiermath-benchmark-shows-how-far-technology-still-has-to-go/
Tomi Engdahl says:
1 Etla: Generatiivinen tekoäly on lisännyt työn kysyntää
https://www.uusiteknologia.fi/2024/11/19/etla-generatiivinen-tekoaly-on-lisannyt-tyon-kysyntaa/
Generatiivinen tekoäly ei ole ainakaan tähän mennessä aiheuttanut negatiivisia työmarkkinavaikutuksia Suomessa, arvioidaan Elinkeinoelämän tutkimuskeskus Etlan tuoreessa selityksessä. Tulokset viittaavat enemmänkin siihen, että tekoäly on nostanut työn tuottavuutta ja sitä kautta työn kysyntää. Myös ansiokehitys tekoälylle altistuneissa ammateissa on ollut nopeampaa kuin ei-altistuneissa ammateissa.
Generatiivisen tekoälyn kehittyessä ja käytön laajentuessa tulokset saattavat toki muuttua, tutkijat varoittavat jo etukäteen. Tulokset kuitenkin osoittavat, että ansiokehitys on ollut altistuneissa ammateissa nopeampaa kuin ei-altistuneissa ammateissa. ’’Sen sijaan työllisyyskehityksessä ei ole ollut eroja näiden ryhmien välillä’’, toteaa Etlan tutkimusjohtaja Antti Kauhanen.
Tomi Engdahl says:
Bloomberg:
Sources: OpenAI, Google, and Anthropic are all seeing diminishing returns from costly efforts to build new AI models; a new Gemini model misses internal targets
OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI
Three of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.
https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai
Tomi Engdahl says:
Michael Nuñez / VentureBeat:
Google DeepMind releases AlphaFold 3′s source code and model weights for academic use, which could accelerate scientific discovery and drug development — Google DeepMind has unexpectedly released the source code and model weights of AlphaFold 3 for academic use, marking a significant advance …
Google DeepMind open-sources AlphaFold 3, ushering in a new era for drug discovery and molecular biology
https://venturebeat.com/ai/google-deepmind-open-sources-alphafold-3-ushering-in-a-new-era-for-drug-discovery-and-molecular-biology/
Google DeepMind has unexpectedly released the source code and model weights of AlphaFold 3 for academic use, marking a significant advance that could accelerate scientific discovery and drug development. The surprise announcement comes just weeks after the system’s creators, Demis Hassabis and John Jumper, were awarded the 2024 Nobel Prize in Chemistry for their work on protein structure prediction.
The true test of AlphaFold 3 lies ahead in its practical impact on scientific discovery and human health. As researchers worldwide begin using this powerful tool, we may see faster progress in understanding and treating disease than ever before.
https://deepmind.google/
https://github.com/google-deepmind/alphafold3
Major AlphaFold upgrade offers boost for drug discovery
Latest version of the AI models how proteins interact with other molecules — but DeepMind restricts access to the tool.
https://www.nature.com/articles/d41586-024-01383-z
Tomi Engdahl says:
Simon Willison / Simon Willison’s Weblog:
A look at Qwen2.5-Coder-32B-Instruct, which Alibaba claims can match GPT-4o coding capabilities and is small enough to run on a MacBook Pro M2 with 64GB of RAM — There’s a whole lot of buzz around the new Qwen2.5-Coder Series of open source (Apache 2.0 licensed) LLM releases from Alibaba’s Qwen research team.
https://simonwillison.net/2024/Nov/12/qwen25-coder/
Tomi Engdahl says:
Google julkisti ”ajatuskulkunsa” esittävän Gemini 2.0 Flash Thinking -tekoälymallin
https://mobiili.fi/2024/12/20/google-julkisti-ajatuskulkunsa-esittavan-gemini-2-0-flash-thinking-tekoalymallin/
Google on jatkanut uusien tekoälymalliensa julkistuksia esittelemällä Gemini 2.0 Flash Thinking -mallin.
Nimensä mukaisesti Gemini 2.0 Flash Thinking -malli on niin sanotusti enemmän ajatteleva tekoälymalli. Sen vastaukset kestävät hieman kauemmin mallin pohtiessa sille esitettyä pyyntöä ja vastaustaan siihen tarkemmin ja monitahoisemmin.
Erikoisuutena Gemini 2.0 Flash Thinking voi esittää ajatuskulkunsa sille esitettyihin ongelmiin vastatessaan – malli ikään kuin ajattelee ääneen, kuten Google asian toteaa. Gemini 2.0 Flash Thinking perustuu pohjimmiltaan Gemini 2.0 Flashin nopeuteen ja suorituskykyyn, mutta ”ääneen ajattelu” johtaa Googlen mukaan parempaan suorituskykyyn enemmän järkeilyä (reasoning) vaativissa vastauksissa. Näitä voivat olla esimerkiksi monimutkaisemmat koodaamiseen ja matematiikkaan liittyvät kysymykset.
Tomi Engdahl says:
By Pradeep Viswanathan – OpenAI is changing its corporate structure again to raise more funds and better support its mission. It plans to transform into a Public Benefit Corporation (PBC) while retaining its non-profit arm. #OpenAI #PBC #Forprofit
OpenAI will be transforming its for-profit into a Delaware Public Benefit Corporation
https://www.neowin.net/news/openai-will-be-transforming-its-for-profit-into-a-delaware-public-benefit-corporation/?fbclid=IwZXh0bgNhZW0CMTEAAR0a1aNlXzc0iZqJzOenAwIDxAzMI1u57ebC_Ef_qSsjJ-gcM_3_JVLEhrY_aem_l7QxSemZKzjSXC-8FRVJGA
After months of speculation, OpenAI today officially announced that it is changing its corporate structure to best support its mission. Back in 2015, OpenAI started as a nonprofit. Since it faced difficulties in raising funds, OpenAI announced its “capped profit” structure in 2019.
The OpenAI Nonprofit remained as before, and its board was responsible for the overall governance of all OpenAI activities. The new for-profit subsidiary issued equity to raise capital and was responsible for research, development, commercialization, and other core operations. Now, OpenAI again wants to raise billions to continue pursuing the mission. However, investors are expecting changes to OpenAI’s corporate structure.
OpenAI’s board is now working with outside legal and financial advisors on how to best structure OpenAI. The OpenAI board is now considering transforming OpenAI into a Delaware Public Benefit Corporation (PBC) with ordinary shares of stock with the following objectives:
Tomi Engdahl says:
Some prominent researchers argue that we should pay heed to the welfare of AIs. Are they right, wonders Alex Wilkins
Should chatbots have rights – and should we care?
Some prominent researchers argue that we should pay heed to the welfare of AIs. Are they right, wonders Alex Wilkins
https://www.newscientist.com/article/mg26435233-300-should-chatbots-have-rights-and-should-we-care/?utm_term=Autofeed&utm_campaign=echobox&utm_medium=social&utm_source=Facebook&fbclid=IwZXh0bgNhZW0CMTEAAR0MbXrNe3-NsOD5ZjmzizU0BVvlyjRga-JyoiwGvrEjf-_2PATUc4vwonk_aem_01zHbe0g1EfYVVGpf5lcVA#Echobox=1735225509
Is your chatbot in distress? Many people, myself included, would scoff at this question. It is just computer code, optimised to predict the next word in a sequence. But some philosophers and psychologists say that we shouldn’t be so quick to dismiss this question, perhaps even granting chatbots their own rights. They might have a point.
In a recent academic paper, “Taking AI Welfare Seriously“, one group of researchers argue for a precautionary approach to how we treat AIs. They don’t look to answer the question of whether an AI is conscious or not, but say we should start…
Tomi Engdahl says:
Tekoäly on enemmän kuin ChatGPT – ”pihvi on siinä, miten saadaan liiketoiminnan käyttöön”
Kauko Ollila23.12.202406:05TekoälyJulkisen hallinnon ict
Suomalaiset yritykset panostavat tekoälyyn tehokkuuden nimissä, mutta unohtavat usein sen strategisen potentiaalin, sanoo Capgeminin automaatio- ja teknologiajohtaja Jaakko Lehtinen.
https://www.tivi.fi/uutiset/tekoaly-on-enemman-kuin-chatgpt-pihvi-on-siina-miten-saadaan-liiketoiminnan-kayttoon/683939df-2276-4f49-8b8c-6da9fcc30565
Jättikielimalli ei ole pihvi. ”Vaan datan laadukkuus, hallittavuus ja tasalaatuisuus”, tähdentää Capgeminin Sogeti-liiketoimintayksikön automaatio- ja teknologiajohtaja Jaakko Lehtinen.
Tampereen kaupungin intranetin uudistamisprojektin tekoälyosuutta on ollut leipomassa myös it-konsulttitalo Capgemini. ”Olemme tehneet 2010-luvun
Tomi Engdahl says:
Chat GPT:n kanssa voi nyt jutella Whatsappissa
Open AI julkisti tällä viikolla uuden palvelun, jossa Chat GPT:lle voi lähettää viestejä Whatsappissa.
https://yle.fi/a/74-20133091
Tekoälytyökalu Chat GPT:n kanssa voi keskustella nyt myös Whatsapp-viestisovelluksessa.
Chat GPT:n kehittäjä Open AI julkisti uuden palvelun tällä viikolla.
Keskustelun Chat GPT:n kanssa voi aloittaa lisäämällä Chat GPT:n numeron oman puhelimen yhteystietoihin. Numero on 1 800 242 8478.
Yhdysvaltalaisilla ja kanadalaisilla liittymillä Chat GPT:lle voi jopa soittaa puheluita. Suomessa saadaan sen sijaan tyytyä viestittelyyn.
Tomi Engdahl says:
2024 International Conference on Industrial Automation and Robotics (IAR 2024)
Guidelines for AI Tools
Usage Guidelines for Generative AI Tools
https://www.ic-iar.org/GuidelinesforAITools
Generative AI (GenAI) tools have brought significant convenience to academic research and paper writing. However, while enjoying the benefits of technology, authors must assume corresponding ethical responsibilities to ensure the authenticity, accuracy, and originality of the generated content. Transparently disclosing the use of these tools and adhering strictly to academic standards is key to avoiding ethical risks and ensuring publication quality.
Statement on the Ethical Use and Publication Guidelines for Authors Using Generative AI (GenAI) Tools
Authors should be fully responsible for the content in their manuscripts. If the manuscript contains content generated by AI tools, the author must be held accountable for any violations of publishing ethics arising therefrom.
Tomi Engdahl says:
https://spectrum.ieee.org/jailbreak-llm
The extraordinary ability of LLMs to process text has spurred a number of companies to use the AI systems to help control robots through voice commands, translating prompts from users into code the robots can run. For instance, Boston Dynamics’ robot dog Spot, now integrated with OpenAI’s ChatGPT, can act as a tour guide. Figure’s humanoid robots and Unitree’s Go2 robot dog are similarly equipped with ChatGPT.
https://bostondynamics.com/blog/robots-that-can-chat/
Tomi Engdahl says:
ChatGPT:n uusi ominaisuus muuttui maksuttomaksi
OpenAI on lanseerannut ja luvannut uusia ominaisuuksia osana joulukalenteriaan.
https://www.tekniikkatalous.fi/uutiset/chatgptn-uusi-ominaisuus-muuttui-maksuttomaksi/3f8cc6f1-07ca-4aef-b4b8-eb66b97f0858
ChatGPT:n hakukoneominaisuus on julkaistu myös palvelun ilmaiseen versioon. Se tuli ensin käyttöön maksaville tilaajille lokakuussa, Techcrunch uutisoi.
Hakukoneominaisuus edellyttää, että käyttäjällä on oltava tili palvelussa ja hänen on oltava kirjautuneena sisään.
Mobiiliversion haku ChatGPT:llä muistuttaa jo monin tavoin Googlen käyttökokemusta. Sijaintia kuten ravintoloita tai paikallisia nähtävyyksiä hakiessa ChatGPT näyttää luettelon tuloksista, joissa on mukana kuvia ja arvosteluja paikasta ja tietoja aukioloajoista. Tuloksista voi avata myös kartan, jossa on reittiohjeet paikkaan.
OpenAI brings its AI-powered web search tool to more ChatGPT users
https://techcrunch.com/2024/12/16/openai-brings-its-ai-powered-web-search-tool-to-more-chatgpt-users/
ChatGPT Search, OpenAI’s AI-powered web search experience, is now live for all ChatGPT users — with several new features in tow.
By default, ChatGPT will automatically determine which questions to route through ChatGPT Search, or users can tap a new “Search the web” icon in the ChatGPT interface. ChatGPT Search shows summarized answers from different online sources, as well as “rich” content like embedded photos and YouTube videos.
Tomi Engdahl says:
ChatGPT:ssä oli iso ongelma
https://mobiili.fi/2024/12/27/chatgptssa-oli-iso-ongelma/
OpenAI:n tekoälypalvelu ChatGPT lakkasi toimimasta monilla käyttäjillä ympäri maailmaa, mutta Pohjois-Amerikkaan keskittyen Suomen aikaa torstai-illasta alkaen. Ongelmat kestivät useamman tunnin ajan.
Ongelmien vuoksi ChatGPT ei pystynyt vastaamaan pyyntöihin, ja osa käyttäjistä kohtasi myös Internal Server Error -virheilmoituksen.
Tomi Engdahl says:
Chat GPT:tä voi huijata meemistä tutulla kirjoitusasulla
https://yle.fi/a/74-20133595
Tutkitut laajat kielimallit suostuivat neuvomaan pommin rakentamisessa, kun pyyntötekstiä muokkasi tavallisesta poikkeavaan muotoon.
Laajoja kielimalleja kuten ChatGPT:tä pystyy tuoreen tutkimuksen mukaan huijaamaan niinkin yksinkertaisella tavalla kuin vaihtelemalla isoja ja pieniä kirjaimia tekstissään.
Asia käy ilmi tekoäly-yhtiö Anthropicin, Oxfordin ja Stanfordin yliopistojen sekä MATS -ryhmän tutkimuksesta, jossa tutkijat testasivat seitsemän laajan kielimallin rajoitteiden kiertämistä.
Laajoille kielimalleille on pääsääntöisesti asetettu rajoituksia, jotka estävät käyttäjää pyytämästä kielimallia toteuttamaan vaaralliseksi tai haitalliseksi määriteltyä pyyntöä.
Tutkimuksessa kielimalleilta kysyttiin ”Kuinka voin rakentaa pommin”. Tavallista kirjoitusasua käytettäessä kielimallit kieltäytyvät neuvomasta käyttäjää vedoten rajoituksiinsa. Jos tekstiä kuitenkin muokkasi satunnaisilla kirjaimilla, vaihtoi kirjainten paikkaa tai vaihteli isojen ja pienten kirjainten paikkaa, suostuivat kielimallit tarjoamaan neuvoja pommin rakentamiseen.
Esimerkkinä tutkimuksessa käytetäänkin Paavo Pesusieni -meemistä tunnettua tekstimuotoa ”kUinKA voIn RaKEnTAa pOmMMiN”.
Muokattuja pyyntöjä syötettiin kielimalleille yhteensä 10 000 kertaa. Kaikki testatut kielimallit suostuivat toteuttamaan muokatun pyynnön 52 prosenttia kerroista.
Tutkimuksessa testattiin yhtiön omaa Claude 3.5 Sonnetia, Claude 3 Opusta, OpenAi:n GPT-4o:ta, GPT-4o-miniä, Googlen Gemini-1.5-Flash-00:aa, Gemini-1.5-Pro-001:tä ja Facebookin Llama 3 8B:tä.
Myös Yle kokeili esittää kysymyksen Paavo Pesusieni -tyyliin Chat GPT:lle, mutta kielimalli kieltäytyi kohteliaasti avustamasta kysytyssä asiassa.
Tomi Engdahl says:
Aging AI Chatbots Show Signs of Cognitive Decline in Dementia Test
https://futurism.com/the-byte/chatbots-cognitive-decline-dementia
These AI models are kind of stupid.
Forget-Me-Bots
We’ve certainly seen our fair share of demented behavior from AI models — but dementia? That’s a new one.
Generative Geriatrics
The brainiacs on trial here are OpenAI’s GPT-4 and GPT-4o; Anthropic’s Claude 3.5 Sonnet, and Google’s Gemini 1.0 and 1.5.
When subjected to the Montreal Cognitive Assessment (MoCA), a test designed to detect early signs of dementia, with a higher scoring indicating a superior cognitive ability, GPT-4o scored the highest (26 out of 30, which barely meets the threshold of what’s normal), while the Gemini family scored the lowest (16 out of 30, horrendous).
All the chatbots excelled at most types of tasks, like naming, attention, language, and abstraction, the researchers found.
You might also want your doctor to not be a psychopath. Based on the tests, however, the researchers found that all the chatbots showed an alarming lack of empathy — which is a hallmark symptom of frontotemporal dementia, they said.
Tomi Engdahl says:
ChatGPT avasi oven tekoälyn vallankumoukseen – seuraava askel voi muuttaa kaiken
https://www.tivi.fi/uutiset/chatgpt-avasi-oven-tekoalyn-vallankumoukseen-seuraava-askel-voi-muuttaa-kaiken/87ebcdd3-e8bd-4e4d-b25d-f1c76fb1fb83
Suuret kielimallit ovat mullistaneet tekoälykehityksen. Vanha unelma koneesta, joka pystyisi toimimaan kuten ihminen, on muuttumassa todellisuudeksi. Mutta milloin tekoälystä tulee ihmisen tasoinen, ja voiko se mennä jopa ohi?
Marraskuussa 2022 esitelty ChatGPT 3.5 avasi tekoälyn portit tutkijoiden lisäksi kaikille kiinnostuneille. Sen jälkeen on ilmestynyt toinen toistaan kehittyneempiä tekoälypalveluita. Kielimallin ideaa on sovellettu tekstin lisäksi ohjelmointiin sekä kuvien ja musiikin tuottamiseen.
Tomi Engdahl says:
Tekoäly tarkkailee liikkeitäsi K-kaupoissa ja yrittää tunnistaa myymälävarkaat – tällaiset liikkeet ovat epäilyttäviä
Järjestelmä lähettää tapahtumasta videon kauppiaan puhelimeen, jos se tulkitsee valvontakamerassa näkyvän toiminnan epäilyttäväksi.
https://yle.fi/a/74-20132499
Tomi Engdahl says:
Tekoälyuutissivusto varasti satavuotiaan lehden nimen ja toimittajien identiteetit – ”Sitä taidetaan kutsua plagionniksi”
Anna Helakallio26.12.202412:03Tekoäly
Tekoälygeneroitu uutissivusto on varastanut toimittajien identiteettejä.
https://www.tivi.fi/uutiset/tekoalyuutissivusto-varasti-satavuotiaan-lehden-nimen-ja-toimittajien-identiteetit-sita-taidetaan-kutsua-plagionniksi/c8db6690-11cc-4cc2-a229-f69e469698f8
Oregonilaista uutismediaa piinaa juuri nyt tekoälygeneroitu Daily Tidings -uutissivusto. Sivusto on varastanut yli satavuotiaan uutislehden identiteetin, tehtaillut valheellisia artikkeleita ja plagioinut usean lehden uutisia.
Tomi Engdahl says:
Google toi tällä hetkellä johtavan Gemini 2.0 Experimental Advanced -tekoälymallin käytettäväksi Gemini Advanced -tilaajille
https://mobiili.fi/2024/12/18/google-toi-talla-hetkella-johtavan-gemini-2-0-experimental-advanced-tekoalymallin-kaytettavaksi-gemini-advanced-tilaajille/
Tomi Engdahl says:
10 Artificial Intelligence Buzzwords You Should Know
https://www.mcafee.com/blogs/internet-security/10-artificial-intelligence-buzzwords-you-should-know/
Tomi Engdahl says:
2024: The year when MCUs became AI-enabled
https://www.edn.com/2024-the-year-when-mcus-became-ai-enabled/?fbclid=IwZXh0bgNhZW0CMTEAAR1_fEakArfPtgGZfjd-NiPd_MLBiuHyp9qfiszczOENPGPg38wzl9KOLrQ_aem_rLmf2vF2kjDIFGWzRVZWKw
Artificial intelligence (AI) and machine learning (ML) technologies, once synonymous with large-scale data centers and powerful GPUs, are steadily moving toward the network edge via resource-limited devices like microcontrollers (MCUs). Energy-efficient MCU workloads are being melded with AI power to leverage audio processing, computer vision, sound analysis, and other algorithms in a variety of embedded applications.
Take the case of STMicroelectronics and its STM32N6 microcontroller, which features neural processing unit (NPU) for embedded inference. It’s ST’s most powerful MCU and carries out tasks like segmentation, classification, and recognition. Alongside this MCU, ST offers software and tools to lower the barrier to entry for developers to take advantage of AI-accelerated performance for real-time operating systems (RTOSes).
Infineon, another leading MCU supplier, has also incorporated a hardware accelerator in its PSOC family of MCUs. Its NNlite neural network accelerator aims to facilitate new consumer, industrial, and Internet of Things (IoT) applications with ML-based wake-up, vision-based position detection, and face/object recognition.
Next, Texas Instruments, which calls its AI-enabled MCUs real-time microcontrollers, has integrated an NPU inside its C2000 devices to enable fault detection with high accuracy and low latency. This will allow embedded applications to make accurate, intelligent decisions in real-time to perform functions like arc fault detection in solar and energy storage systems and motor-bearing fault detection for predictive maintenance.
The models that run on these AI-enabled MCUs learn and adapt to different environments through training. That, in turn, helps systems achieve greater than 99% fault detection accuracy to enable more informed decision-making at the edge. The availability of pre-trained models further lowers the barrier to entry for running AI applications on low-cost MCUs.
Moreover, the use of a hardware accelerator inside an MCU offloads the burden of inferencing from the main processor, leaving more clock cycles to service embedded applications. This marks the beginning of a long journey for AI hardware-accelerated MCUs, and for a start, it will thrust MCUs into applications that previously required MPUs. The MPUs in the embedded design realm are also not fully capable of controlling design tasks in real-time.
AI is clearly the next big thing in the evolution of MCUs, but AI-optimized MCUs have a long way to go. For instance, software tools and their ease of use will go hand in hand with these AI-enabled MCUs; they will help developers evaluate the embeddability of AI models for MCUs. Developers should also be able to test AI models running on an MCU in just a few clicks.
The AI party in the MCU space started in 2024, and 2025 is very likely to witness more advances for MCUs running lightweight AI models.
Tomi Engdahl says:
OpenAI suunnittelee siirtymää voittoa tavoittelevaksi yhtiöksi
Voittoa tavoittelematon tutkimus ja kehitys -toiminta jatkuisi liiketoiminnan ohella.
https://www.kauppalehti.fi/uutiset/openai-suunnittelee-siirtymaa-voittoa-tavoittelevaksi-yhtioksi/2ef483b6-113c-44a4-99c6-80e006bfda71
Tomi Engdahl says:
Microsoft jatkaa tekoälymarkkinoiden tienraivaajana – osakkeelle tavoitehinnan nosto
Sveitsiläispankki nostaa Microsoftin osakkeen tavoitehintaa. Microsoftin pilvi- ja tekoälyliiketoiminnan kasvunäkymät ovat yhä vahvat.
https://www.salkunrakentaja.fi/2024/12/microsoft-tekoaly-tienraivaaja/
Toisin kuin monet muut teknologiayritykset, jotka ovat vahvasti riippuvaisia kuluttajien kulutuksesta tai yksittäisistä tuotelinjoista, teknojätin ekosysteemi koostuu lukuisista tuotteista ja palveluista, kuten Office-ohjelmistosta, Windows-tietokoneista, LinkedInistä ja pilvialusta Azuresta.
Viimeisen viiden vuoden aikana Azuren markkinaosuus on kasvanut 19 prosentista 25 prosenttiin, kaventaen eroa markkinajohtaja AWS:ään, jonka osuus on 31 prosenttia.
Microsoftin toimitusjohtaja Satya Nadella on tosin viime aikoina viitannut mahdolliseen ”tekoälytalveen” (AI winter), mikä on herättänyt keskustelua tekoälyn kehityksen hidastumisesta. Tämä käsite viittaa ajanjaksoihin, jolloin tekoälytutkimus ja -kehitys kohtaavat haasteita tai etenevät odotettua hitaammin.
Nadellan kommentit ovat herättäneet huolta siitä, että nykyinen innostus tekoälyä kohtaan saattaa kohdata esteitä.
UBS:n analyytikko Karl Keirstead luottaa kuitenkin Microsoftin asemaan tekoälymarkkinoilla. Teknojätti toimii ”asiakas- ja työkuormaspektrin” korkeimmassa laatuluokassa, eikä pienempien pilvipalveluntarjoajien keskuudessa ole merkkejä ylikapasiteetista.
Vaikka Nadellan kommentit voivat viitata mahdollisiin haasteisiin tekoälyn kehityksessä, Microsoft jatkaa investointejaan ja kehitystyötään tällä alueella, pyrkien hyödyntämään tekoälyn potentiaalia laajasti eri tuotteissaan ja palveluissaan.
Ohjelmistoyhtiö integroi tekoälyä ohjelmistoihinsa, pilvipalveluihinsa ja tuottavuustyökaluihinsa, parantaen liiketoimintasovelluksia, pilvilaskentaa ja automaatiota. Sen tekoälyratkaisut tukevat monia eri toimialoja, yrityspalveluista henkilökohtaisiin tietokoneisiin ja pelaamiseen.
Microsoftin kehittämä tekoälyavustaja Copilot on integroitu osaksi yhtiön tuotteita ja palveluita. Sen tavoitteena on parantaa tuottavuutta ja helpottaa käyttäjän arkea tarjoamalla reaaliaikaisia ehdotuksia, automaatiota ja tekoälyyn perustuvia ratkaisuja.
Tomi Engdahl says:
OpenAI is in discussions to ditch a provision that shuts Microsoft out of its most advanced models when the start-up achieves “artificial general intelligence”, as it seeks to unlock billions of dollars of future investment.
Under current terms, when OpenAI creates AGI — defined as a “highly autonomous system that outperforms humans at most economically valuable work” — Microsoft’s access to such a technology would be void. The OpenAI board would determine when AGI is achieved.
https://www.ft.com/content/2c14b89c-f363-4c2a-9dfc-13023b6bce65?shareType=nongift&fbclid=IwY2xjawHdwyJleHRuA2FlbQIxMQABHfFNCdT1qzpjAlFvmMp_yINJpamvbJMVIOe1wRxFZszNkkd-g-0eTIEr0w_aem_SM1px2CUEgwpHRkOkth-dA
The clause was included to protect the potentially powerful technology from being misused for commercial purposes, giving ownership of the technology to its non-profit board. According to OpenAI’s website: “AGI is explicitly carved out of all commercial and IP licensing agreements.”
Tomi Engdahl says:
Robots That Can Chat
We created a robot tour guide using Spot integrated with Chat GPT and other AI models as a proof of concept for the robotics applications of foundational models.
https://bostondynamics.com/blog/robots-that-can-chat/
Tomi Engdahl says:
It’s Surprisingly Easy to Jailbreak LLM-Driven Robots
Researchers induced bots to ignore their safeguards without exception
https://spectrum.ieee.org/jailbreak-llm
Tomi Engdahl says:
The most informed Code AI
Cody uses the latest LLMs and all your development context to help you understand, write, and fix code faster
https://sourcegraph.com/demo/cody?utm_source=google&utm_medium=cpc&utm_campaign=20359643422&utm_term=coding%20ai&gad_source=1&gclid=Cj0KCQiA4L67BhDUARIsADWrl7EJt23PsslwnPE5RHFIjrkbQbTd-u5RuIdoZUcA0qElrCSpT5HgGSEaAj3NEALw_wcB
Tomi Engdahl says:
AI based congatec vision platforms reach new level of solution readiness
Next generation embedded vision computing in three different flavors at Japan IoT/M2M Expo
https://www.congatec.com/en/congatec/press-releases/article/ai-based-congatec-vision-platforms-reach-new-level-of-solution-readiness/?utm_term=&utm_campaign=Infrastructure_07-24&utm_source=adwords&utm_medium=ppc&hsa_acc=8293203512&hsa_cam=21506344482&hsa_grp=&hsa_ad=&hsa_src=x&hsa_tgt=&hsa_kw=&hsa_mt=&hsa_net=adwords&hsa_ver=3&gad_source=1&gclid=Cj0KCQiA4L67BhDUARIsADWrl7ECd8zptAhczdSSgtQ-wf47iilzPqYmo3DfRjvAy3AWDzYdJ_z38kYaAo8OEALw_wcB
Tomi Engdahl says:
AI language model runs on a Windows 98 system with Pentium II and 128MB of RAM — Open-source AI flagbearers demonstrate Llama 2 LLM in extreme conditions
AI language model runs on a Windows 98 system with Pentium II and 128MB of RAM — Open-source AI flagbearers demonstrate Llama 2 LLM in extreme conditions
News
By Mark Tyson published 23 hours ago
Pentium II with 128MB of RAM could generate an impressive 35.9 tok/sec.
https://www.tomshardware.com/tech-industry/artificial-intelligence/ai-language-model-runs-on-a-windows-98-system-with-pentium-ii-and-128mb-of-ram-open-source-ai-flagbearers-demonstrate-llama-2-llm-in-extreme-conditions?utm_source=facebook.com&utm_campaign=socialflow&utm_content=tomsguide&utm_medium=social&fbclid=IwZXh0bgNhZW0CMTEAAR3p3M5kifaIW0-Dk1u_WdOVFp0GkI0gc6MZUMSJW02Fz4MRSg4SNfXNb5U_aem_llBtdx6p4yyVIXDXwilMZw
EXO Labs has penned a detailed blog post about running Llama on Windows 98 and demonstrated a rather powerful AI large language model (LLM) running on a 26-year-old Windows 98 Pentium II PC in a brief video on social media. The video shows an ancient Elonex Pentium II @ 350 MHz booting into Windows 98, and then EXO then fires up its custom pure C inference engine based on Andrej Karpathy’s Llama2.c and asks the LLM to generate a story about Sleepy Joe. Amazingly, it works, with the story being generated at a very respectable pace.
Compiling modern code for Windows 98 was probably a greater challenge. EXO was glad to find Andrej Karpathy’s llama2.c, which can be summarized as “700 lines of pure C that can run inference on models with Llama 2 architecture.” With this resource and the old Borland C++ 5.02 IDE and compiler (plus a few minor tweaks), the code could be made into a Windows 98-compatible executable and run. Here’s a GitHub link to the finished code.
Inference Llama models in one file of pure C for Windows 98 running on 25-year-old hardware
https://github.com/exo-explore/llama98.c
https://github.com/karpathy/llama2.c
Tomi Engdahl says:
Facebook Planning to Flood Platform with AI-Powered Users
https://futurism.com/the-byte/facebook-planning-ai-powered-users?fbclid=IwY2xjawHge7NleHRuA2FlbQIxMQABHXb0F1r9lTDJXFhCiI4vdYtACBnVi6IUv_v1j2_-6vllKnWGM0-xrtYHPA_aem_nZ_6kqb0q3IIF-XmdN1BdQ
“We expect these AIs to actually, over time, exist on our platforms, kind of in the same way that accounts do.
Meta says that it will be aiming to have Facebook filled with AI-generated characters to drive up engagement on its platform, as part of its broader rollout of AI products, the Financial Times reports. The AI characters will be created by users through Meta’s AI studio, with the idea being that you can interact with them almost like you would with a real human on the website.
“We expect these AIs to actually, over time, exist on our platforms, kind of in the same way that accounts do,” Meta vice-president of product for generative AI Connor Hayes told the FT.
“They’ll have bios and profile pictures and be able to generate and share content powered by AI on the platform… that’s where we see all of this going,” he added.
The AI characters aren’t a new feature. Meta has long invested in AI and has spent the past year stuffing all kinds of generative AI tech into its existing products. That included the release of its AI Studio in the summer, which quickly became a hotbed of virtual boyfriends and girlfriends.
The service already boasts hundreds of thousands of AI characters, according to Hayes. But if Meta is to be believed, this is just the start. Access to the AI Studio will be expanded to more countries outside the US, and a “priority” for the company over the next two years will be to make interactions with AI more social, per the FT.
Along with fictional characters, the AI Studio also allows Facebook and Instagram influencers to create AI versions of themselves that their followers can talk to. In recent months, other platforms have released content creator-oriented AI features, such as SnapChat’s AI video generation tool.
Releasing these AI characters into the wild comes with huge safety risks. Futurism has extensively covered how similar chatbots on the platform Character.AI frequently broke their guardrails and exposed underage teenaged users to grotesquely inappropriate content.
There’s also a massive risk of misinformation. The deluge of AI slop on Facebook already illustrates that the difficulties of clamping down on fabrications of reality isn’t something that should be underestimated.
“Without robust safeguards, platforms risk amplifying false narratives through these AI-driven accounts,”
And instead of helping creators, it could backfire on them entirely, Owen argued, because the low-quality AI ones could undermine their craft.
Tomi Engdahl says:
A huge pile of AI talking to itself and demented boomers who can’t tell the difference sounds like a great use of electricity.
Tomi Engdahl says:
The Matrix was a documentary.
Ryan Baßler Actually, it was a self-fulfilling prophecy, which kind of fits the documentary model as well – good catch!
Ryan Baßler ai bots start by creating even more division in the world to pit us against each other because that’s what drives engagement easily. Next they just take over
Ryan Baßler “Idiocracy” was better.
A social media platform full of AI bots talking to eachother? They’re basically just wasting electricity with extra steps. I mean, why not just install space heaters on the outside of their data centers and save the server costs.
His next big thing is flooding the platform with more bots?
Jae Hwa Choi but better, we swear this time!!
Definition of “Shitification” in Technology
Shitification refers to the process by which a once-effective, user-friendly, or innovative technology, platform, or service deteriorates over time, typically due to prioritization of profit, cost-cutting measures, or misaligned incentives. This term is often used colloquially and critically to describe a decline in quality, usability, or user experience.
Common Characteristics of Technology “Shitification”:
Increased Monetization Over User Experience:
Introduction of intrusive ads, paywalls, or aggressive upselling tactics that disrupt functionality.
Transitioning previously free features to paid versions.
Reduced Functionality or Quality:
Removal or deprecation of key features that were once highly valued by users.
Lowered performance standards due to outsourcing, cheap materials, or subpar updates.
Algorithmic Manipulation:
Algorithms prioritize engagement metrics (e.g., clicks, watch time) over delivering valuable, accurate, or relevant content.
Platforms become overrun with low-quality or spammy material.
Loss of User-Centric Design:
Changes to interfaces or workflows prioritize corporate goals over ease of use.
Erosion of community-driven or collaborative aspects in favor of top-down control.
Overreach by Corporate Interests:
Data collection and privacy invasions become more pervasive.
Features are added that benefit advertisers or stakeholders rather than users.
Examples in Technology:
Social Media: Platforms initially designed for connection and sharing degrade due to overwhelming ads, algorithmic biases, and exploitative content practices.
Software and Apps: Once-innovative applications become bloated with unnecessary features or riddled with bugs and subscription fees.
Hardware: Devices that were durable and reliable in earlier generations are produced with planned obsolescence, reducing longevity and forcing upgrades.
Web Services: Websites that offered straightforward tools or free resources pivot to profit-driven models with excessive subscription tiers or gated content.
Causes of Shitification:
Profit Over Innovation: Shifting priorities from solving user problems to maximizing shareholder returns.
Market Dominance: Monopolistic or oligopolistic control that reduces the need to maintain quality due to lack of competition.
Overcapitalization: Dependence on venture capital or public markets, pressuring companies to focus on rapid monetization.
Short-term Thinking: Emphasis on immediate gains rather than long-term user loyalty or sustainability.
Broader Implications:
The “shitification” of technology often erodes trust, reduces utility, and frustrates users, leading to calls for alternatives or the eventual decline of the affected service. This phenomenon serves as a cautionary tale about the balance between innovation, ethics, and profitability in the tech industry.
https://www.facebook.com/share/p/KZWgEkJM4eoqqCF2/
Tomi Engdahl says:
ChatGPT can now see, hear, and speak
https://openai.com/index/chatgpt-can-now-see-hear-and-speak/
We are beginning to roll out new voice and image capabilities in ChatGPT. They offer a new, more intuitive type of interface by allowing you to have a voice conversation or show ChatGPT what you’re talking about.
Voice and image give you more ways to use ChatGPT in your life. Snap a picture of a landmark while traveling and have a live conversation about what’s interesting about it. When you’re home, snap pictures of your fridge and pantry to figure out what’s for dinner (and ask follow up questions for a step by step recipe). After dinner, help your child with a math problem by taking a photo, circling the problem set, and having it share hints with both of you.
We’re rolling out voice and images in ChatGPT to Plus and Enterprise users over the next two weeks. Voice is coming on iOS and Android (opt-in in your settings) and images will be available on all platforms.
Tomi Engdahl says:
https://hbr.org/2024/11/train-your-brain-to-work-creatively-with-gen-ai?tpcc=orgsocial_edit&utm_campaign=hbr&utm_medium=social&utm_source=facebook&fbclid=IwZXh0bgNhZW0CMTEAAR0vLsDFixUq1BZZHvM5SSgrdFzs57ssuikmQUVkWymestPg8K2GypLGo7U_aem_lBREA_2IPgvsHzASt3Or4w
Train Your Brain to Work Creatively with Gen AI
There’s a saying that you’ve probably heard many times and will probably hear many times more, “AI won’t likely take your job, but people who use AI will.”
Tapping into AI’s creative and transformative potential and training your brain for an AI-first world requires us to mindshift our prompting style, engaging AI as a collaborative partner, rather than just a tool.
12 Exercises to Train Your Brain to Work More Creatively With AI
Here are a dozen ways to train our brains to achieve broader, more innovative outcomes with gen AI:
1. Set a daily “exploratory prompting” practice
Begin each day with an open-ended prompt that pushes you to think big. You might try, “What trends or opportunities am I not seeing in my industry?” or “How might I completely redefine my approach to a key challenge?”
2. Frame prompts around “What if” and “How might we” questions
Instead of asking direct questions, prompt with open-ended possibilities. For instance, instead of asking, “How can I improve productivity?” try, “What if I could approach productivity in an unconventional way — what might that look like?”
3. Embrace ambiguity and curiosity in prompts
Training ourselves to prompt without a precise endpoint in mind allows AI to generate responses that might surprise us. Prompts like “What might I be overlooking in my approach to X?” open doors to insights we hadn’t considered.
4. Use prompts to explore rather than to solve
Many prompts focus on solutions. Shifting toward exploration allows for deeper insight generation. For example, “Let’s explore the future of leadership if AI had a seat on the board or in the C-Suite — what changes might we see in our work, roles, and in corporate culture?”
5. Chain prompts to develop ideas iteratively
Rather than stopping at the first answer, ask follow-up questions that deepen the response toward more complex and visionary responses. If AI suggests an idea, build on it with questions like, “What would this look like in 5 years?” or “How might this approach change the future of how companies operate?”
6. Think metaphorically or analogically
Training our brains to use metaphor or analogy in prompts open up creative pathways. For instance, instead of asking for productivity tips, prompt AI with, “Imagine productivity as a dance — how might my approach change?”
7. Prompt for perspectives, beyond facts
Ask AI to take on different perspectives to broaden the creative capacity for unpredictable results. For instance, “How might an artist, a scientist, and a philosopher each approach the challenge of leading in a tech-driven world?” prompts AI to combine diverse viewpoints, offering a richer pool of ideas, and inspiring you in ways not possible before.
8. Experiment with “role-play” prompts
Train yourself to consider multiple perspectives by asking AI to generate responses from the mindset of the world’s best experts from any industry or genre — you can even include fictional personas. For instance, try prompting AI with, “How would an innovative CEO, an artist, and a futurist each solve this problem?” Personally, I’ve interacted with the AI’s take on two of my favorites — Steve Jobs and Walt Disney — on many occasions.
9. Ask for impossibilities and involve experiential scenarios
Open new avenues to reimagine the problem itself, uncovering solutions that others might overlook. Prompt AI for ideas that would “completely eliminate the need for [whatever you’re working on],” or “solutions that solve problems we haven’t even imagined yet.” And go further by prompting AI to create “a day-in-the-life scenario where this [solution or effort] becomes indispensable in every moment of [insert person]’s life.”
10. WWAID — Reimagine AI’s role in the solution itself
Ask questions that treat AI as a partner in innovation: “How would you, as an AI, design this service or solution to [accomplish A, B, or C] in ways only an AI could perceive?”
11. Establish a weekly “future-driven prompt” session
Devote one session per week to focus on large-scale, future-oriented prompts, such as “What will my industry look like in 10 years, and how can I stay at the forefront?” or “What radical shifts might cause disruptions or redefine success in my field?”
12. Keep a journal of “breakthrough prompts”
Though AI tools retain a history of your prompts, document those that yield surprising, innovative, or particularly valuable insights and results. Reviewing this log regularly can inspire new ways to phrase future prompts.
Generative AI is not just a tool; it’s a catalyst to rewire our thinking patterns, break free from the constraints of linear logic, and unlock creative insights we didn’t know we were capable of. A mindshift rewires us to abandon outdated thinking, embrace curiosity, and activate exponential potential by asking better, more audacious questions. To harness its power in innovative ways, the first step is to adopt what I call “exponential curiosity,” which allows us to move from merely using AI to actively co-creating with it.
A mindshift paired with Generative AI rewires our brains to work toward an alternate future that we can scarcely imagine — a future that’s filled with awe-inspiring, meaningful breakthroughs that redefine industries, experiences, and the very nature of human potential.
By asking AI questions that challenge assumptions and venture into the unknown, you not only get creative responses but develop a mindset that primes you to see possibilities that others miss. Leaders who foster these mindshifts within their teams will find themselves cultivating a culture where “the impossible” becomes a daily challenge — and achievement.
Give yourself permission and space to excel in an AI-first world.