AI is developing all the time. Here are some picks from several articles what is expected to happen in AI and around it in 2025. Here are picks from various articles, the texts are picks from the article edited and in some cases translated for clarity.
AI in 2025: Five Defining Themes
https://news.sap.com/2025/01/ai-in-2025-defining-themes/
Artificial intelligence (AI) is accelerating at an astonishing pace, quickly moving from emerging technologies to impacting how businesses run. From building AI agents to interacting with technology in ways that feel more like a natural conversation, AI technologies are poised to transform how we work.
But what exactly lies ahead?
1. Agentic AI: Goodbye Agent Washing, Welcome Multi-Agent Systems
AI agents are currently in their infancy. While many software vendors are releasing and labeling the first “AI agents” based on simple conversational document search, advanced AI agents that will be able to plan, reason, use tools, collaborate with humans and other agents, and iteratively reflect on progress until they achieve their objective are on the horizon. The year 2025 will see them rapidly evolve and act more autonomously. More specifically, 2025 will see AI agents deployed more readily “under the hood,” driving complex agentic workflows.
In short, AI will handle mundane, high-volume tasks while the value of human judgement, creativity, and quality outcomes will increase.
2. Models: No Context, No Value
Large language models (LLMs) will continue to become a commodity for vanilla generative AI tasks, a trend that has already started. LLMs are drawing on an increasingly tapped pool of public data scraped from the internet. This will only worsen, and companies must learn to adapt their models to unique, content-rich data sources.
We will also see a greater variety of foundation models that fulfill different purposes. Take, for example, physics-informed neural networks (PINNs), which generate outcomes based on predictions grounded in physical reality or robotics. PINNs are set to gain more importance in the job market because they will enable autonomous robots to navigate and execute tasks in the real world.
Models will increasingly become more multimodal, meaning an AI system can process information from various input types.
3. Adoption: From Buzz to Business
While 2024 was all about introducing AI use cases and their value for organizations and individuals alike, 2025 will see the industry’s unprecedented adoption of AI specifically for businesses. More people will understand when and how to use AI, and the technology will mature to the point where it can deal with critical business issues such as managing multi-national complexities. Many companies will also gain practical experience working for the first time through issues like AI-specific legal and data privacy terms (compared to when companies started moving to the cloud 10 years ago), building the foundation for applying the technology to business processes.
4. User Experience: AI Is Becoming the New UI
AI’s next frontier is seamlessly unifying people, data, and processes to amplify business outcomes. In 2025, we will see increased adoption of AI across the workforce as people discover the benefits of humans plus AI.
This means disrupting the classical user experience from system-led interactions to intent-based, people-led conversations with AI acting in the background. AI copilots will become the new UI for engaging with a system, making software more accessible and easier for people. AI won’t be limited to one app; it might even replace them one day. With AI, frontend, backend, browser, and apps are blurring. This is like giving your AI “arms, legs, and eyes.”
5. Regulation: Innovate, Then Regulate
It’s fair to say that governments worldwide are struggling to keep pace with the rapid advancements in AI technology and to develop meaningful regulatory frameworks that set appropriate guardrails for AI without compromising innovation.
12 AI predictions for 2025
This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.
https://www.cio.com/article/3630070/12-ai-predictions-for-2025.html
This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.
1. Small language models and edge computing
Most of the attention this year and last has been on the big language models — specifically on ChatGPT in its various permutations, as well as competitors like Anthropic’s Claude and Meta’s Llama models. But for many business use cases, LLMs are overkill and are too expensive, and too slow, for practical use.
“Looking ahead to 2025, I expect small language models, specifically custom models, to become a more common solution for many businesses,”
2. AI will approach human reasoning ability
In mid-September, OpenAI released a new series of models that thinks through problems much like a person would, it claims. The company says it can achieve PhD-level performance in challenging benchmark tests in physics, chemistry, and biology. For example, the previous best model, GPT-4o, could only solve 13% of the problems on the International Mathematics Olympiad, while the new reasoning model solved 83%.
If AI can reason better, then it will make it possible for AI agents to understand our intent, translate that into a series of steps, and do things on our behalf, says Gartner analyst Arun Chandrasekaran. “Reasoning also helps us use AI as more of a decision support system,”
3. Massive growth in proven use cases
This year, we’ve seen some use cases proven to have ROI, says Monteiro. In 2025, those use cases will see massive adoption, especially if the AI technology is integrated into the software platforms that companies are already using, making it very simple to adopt.
“The fields of customer service, marketing, and customer development are going to see massive adoption,”
4. The evolution of agile development
The agile manifesto was released in 2001 and, since then, the development philosophy has steadily gained over the previous waterfall style of software development.
“For the last 15 years or so, it’s been the de-facto standard for how modern software development works,”
5. Increased regulation
At the end of September, California governor Gavin Newsom signed a law requiring gen AI developers to disclose the data they used to train their systems, which applies to developers who make gen AI systems publicly available to Californians. Developers must comply by the start of 2026.
There are also regulations about the use of deep fakes, facial recognition, and more. The most comprehensive law, the EU’s AI Act, which went into effect last summer, is also something that companies will have to comply with starting in mid-2026, so, again, 2025 is the year when they will need to get ready.
6. AI will become accessible and ubiquitous
With gen AI, people are still at the stage of trying to figure out what gen AI is, how it works, and how to use it.
“There’s going to be a lot less of that,” he says. But gen AI will become ubiquitous and seamlessly woven into workflows, the way the internet is today.
7. Agents will begin replacing services
Software has evolved from big, monolithic systems running on mainframes, to desktop apps, to distributed, service-based architectures, web applications, and mobile apps. Now, it will evolve again, says Malhotra. “Agents are the next phase,” he says. Agents can be more loosely coupled than services, making these architectures more flexible, resilient and smart. And that will bring with it a completely new stack of tools and development processes.
8. The rise of agentic assistants
In addition to agents replacing software components, we’ll also see the rise of agentic assistants, adds Malhotra. Take for example that task of keeping up with regulations.
Today, consultants get continuing education to stay abreast of new laws, or reach out to colleagues who are already experts in them. It takes time for the new knowledge to disseminate and be fully absorbed by employees.
“But an AI agent can be instantly updated to ensure that all our work is compliant with the new laws,” says Malhotra. “This isn’t science fiction.”
9. Multi-agent systems
Sure, AI agents are interesting. But things are going to get really interesting when agents start talking to each other, says Babak Hodjat, CTO of AI at Cognizant. It won’t happen overnight, of course, and companies will need to be careful that these agentic systems don’t go off the rails.
Companies such as Sailes and Salesforce are already developing multi-agent workflows.
10. Multi-modal AI
Humans and the companies we build are multi-modal. We read and write text, we speak and listen, we see and we draw. And we do all these things through time, so we understand that some things come before other things. Today’s AI models are, for the most part, fragmentary. One can create images, another can only handle text, and some recent ones can understand or produce video.
11. Multi-model routing
Not to be confused with multi-modal AI, multi-modal routing is when companies use more than one LLM to power their gen AI applications. Different AI models are better at different things, and some are cheaper than others, or have lower latency. And then there’s the matter of having all your eggs in one basket.
“A number of CIOs I’ve spoken with recently are thinking about the old ERP days of vendor lock,” says Brett Barton, global AI practice leader at Unisys. “And it’s top of mind for many as they look at their application portfolio, specifically as it relates to cloud and AI capabilities.”
Diversifying away from using just a single model for all use cases means a company is less dependent on any one provider and can be more flexible as circumstances change.
12. Mass customization of enterprise software
Today, only the largest companies, with the deepest pockets, get to have custom software developed specifically for them. It’s just not economically feasible to build large systems for small use cases.
“Right now, people are all using the same version of Teams or Slack or what have you,” says Ernst & Young’s Malhotra. “Microsoft can’t make a custom version just for me.” But once AI begins to accelerate the speed of software development while reducing costs, it starts to become much more feasible.
9 IT resolutions for 2025
https://www.cio.com/article/3629833/9-it-resolutions-for-2025.html
1. Innovate
“We’re embracing innovation,”
2. Double down on harnessing the power of AI
Not surprisingly, getting more out of AI is top of mind for many CIOs.
“I am excited about the potential of generative AI, particularly in the security space,”
3. And ensure effective and secure AI rollouts
“AI is everywhere, and while its benefits are extensive, implementing it effectively across a corporation presents challenges. Balancing the rollout with proper training, adoption, and careful measurement of costs and benefits is essential, particularly while securing company assets in tandem,”
4. Focus on responsible AI
The possibilities of AI grow by the day — but so do the risks.
“My resolution is to mature in our execution of responsible AI,”
“AI is the new gold and in order to truly maximize it’s potential, we must first have the proper guardrails in place. Taking a human-first approach to AI will help ensure our state can maintain ethics while taking advantage of the new AI innovations.”
5. Deliver value from generative AI
As organizations move from experimenting and testing generative AI use cases, they’re looking for gen AI to deliver real business value.
“As we go into 2025, we’ll continue to see the evolution of gen AI. But it’s no longer about just standing it up. It’s more about optimizing and maximizing the value we’re getting out of gen AI,”
6. Empower global talent
Although harnessing AI is a top objective for Morgan Stanley’s Wetmur, she says she’s equally committed to harnessing the power of people.
7. Create a wholistic learning culture
Wetmur has another talent-related objective: to create a learning culture — not just in her own department but across all divisions.
8. Deliver better digital experiences
Deltek’s Cilsick has her sights set on improving her company’s digital employee experience, believing that a better DEX will yield benefits in multiple ways.
Cilsick says she first wants to bring in new technologies and automation to “make things as easy as possible,” mirroring the digital experiences most workers have when using consumer technologies.
“It’s really about leveraging tech to make sure [employees] are more efficient and productive,”
“In 2025 my primary focus as CIO will be on transforming operational efficiency, maximizing business productivity, and enhancing employee experiences,”
9. Position the company for long-term success
Lieberman wants to look beyond 2025, saying another resolution for the year is “to develop a longer-term view of our technology roadmap so that we can strategically decide where to invest our resources.”
“My resolutions for 2025 reflect the evolving needs of our organization, the opportunities presented by AI and emerging technologies, and the necessity to balance innovation with operational efficiency,”
Lieberman aims to develop AI capabilities to automate routine tasks.
“Bots will handle common inquiries ranging from sales account summaries to HR benefits, reducing response times and freeing up resources for strategic initiatives,”
Not just hype — here are real-world use cases for AI agents
https://venturebeat.com/ai/not-just-hype-here-are-real-world-use-cases-for-ai-agents/
Just seven or eight months ago, when a customer called in to or emailed Baca Systems with a service question, a human agent handling the query would begin searching for similar cases in the system and analyzing technical documents.
This process would take roughly five to seven minutes; then the agent could offer the “first meaningful response” and finally begin troubleshooting.
But now, with AI agents powered by Salesforce, that time has been shortened to as few as five to 10 seconds.
Now, instead of having to sift through databases for previous customer calls and similar cases, human reps can ask the AI agent to find the relevant information. The AI runs in the background and allows humans to respond right away, Russo noted.
AI can serve as a sales development representative (SDR) to send out general inquires and emails, have a back-and-forth dialogue, then pass the prospect to a member of the sales team, Russo explained.
But once the company implements Salesforce’s Agentforce, a customer needing to modify an order will be able to communicate their needs with AI in natural language, and the AI agent will automatically make adjustments. When more complex issues come up — such as a reconfiguration of an order or an all-out venue change — the AI agent will quickly push the matter up to a human rep.
Open Source in 2025: Strap In, Disruption Straight Ahead
Look for new tensions to arise in the New Year over licensing, the open source AI definition, security and compliance, and how to pay volunteer maintainers.
https://thenewstack.io/open-source-in-2025-strap-in-disruption-straight-ahead/
The trend of widely used open source software moving to more restrictive licensing isn’t new.
In addition to the demands of late-stage capitalism and impatient investors in companies built on open source tools, other outside factors are pressuring the open source world. There’s the promise/threat of generative AI, for instance. Or the shifting geopolitical landscape, which brings new security concerns and governance regulations.
What’s ahead for open source in 2025?
More Consolidation, More Licensing Changes
The Open Source AI Debate: Just Getting Started
Security and Compliance Concerns Will Rise
Paying Maintainers: More Cash, Creativity Needed
Kyberturvallisuuden ja tekoälyn tärkeimmät trendit 2025
https://www.uusiteknologia.fi/2024/11/20/kyberturvallisuuden-ja-tekoalyn-tarkeimmat-trendit-2025/
1. Cyber infrastructure will be centered on a single, unified security platform
2. Big data will give an edge against new entrants
3. AI’s integrated role in 2025 means building trust, governance engagement, and a new kind of leadership
4. Businesses will adopt secure enterprise browsers more widely
5. AI’s energy implications will be more widely recognized in 2025
6. Quantum realities will become clearer in 2025
7. Security and marketing leaders will work more closely together
Presentation: For 2025, ‘AI eats the world’.
https://www.ben-evans.com/presentations
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.
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. 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.
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.
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.
7 Splunk Predictions for 2025
https://www.splunk.com/en_us/form/future-predictions.html
AI: Projects must prove their worth to anxious boards or risk defunding, and LLMs will go small to reduce operating costs and environmental impact.
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
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
It Costs So Much to Run ChatGPT That OpenAI Is Losing Money on $200 ChatGPT Pro Subscriptions
https://futurism.com/the-byte/openai-chatgpt-pro-subscription-losing-money?fbclid=IwY2xjawH8epVleHRuA2FlbQIxMQABHeggEpKe8ZQfjtPRC0f2pOI7A3z9LFtFon8lVG2VAbj178dkxSQbX_2CJQ_aem_N_ll3ETcuQ4OTRrShHqNGg
In a post on X-formerly-Twitter, CEO Sam Altman admitted an “insane” fact: that the company is “currently losing money” on ChatGPT Pro subscriptions, which run $200 per month and give users access to its suite of products including its o1 “reasoning” model.
“People use it much more than we expected,” the cofounder wrote, later adding in response to another user that he “personally chose the price and thought we would make some money.”
Though Altman didn’t explicitly say why OpenAI is losing money on these premium subscriptions, the issue almost certainly comes down to the enormous expense of running AI infrastructure: the massive and increasing amounts of electricity needed to power the facilities that power AI, not to mention the cost of building and maintaining those data centers. Nowadays, a single query on the company’s most advanced models can cost a staggering $1,000.
Tekoäly edellyttää yhä nopeampia verkkoja
https://etn.fi/index.php/opinion/16974-tekoaely-edellyttaeae-yhae-nopeampia-verkkoja
A resilient digital infrastructure is critical to effectively harnessing telecommunications networks for AI innovations and cloud-based services. The increasing demand for data-rich applications related to AI requires a telecommunications network that can handle large amounts of data with low latency, writes Carl Hansson, Partner Solutions Manager at Orange Business.
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://www.bloomberg.com/opinion/articles/2024-11-20/ai-slowdown-is-everyone-else-s-opportunity
Näin sirumarkkinoilla käy ensi vuonna
https://etn.fi/index.php/13-news/16984-naein-sirumarkkinoilla-kaey-ensi-vuonna
The growing demand for high-performance computing (HPC) for artificial intelligence and HPC computing continues to be strong, with the market set to grow by more than 15 percent in 2025, IDC estimates in its recent Worldwide Semiconductor Technology Supply Chain Intelligence report.
IDC predicts eight significant trends for the chip market by 2025.
1. AI growth accelerates
2. Asia-Pacific IC Design Heats Up
3. TSMC’s leadership position is strengthening
4. The expansion of advanced processes is accelerating.
5. Mature process market recovers
6. 2nm Technology Breakthrough
7. Restructuring the Packaging and Testing Market
8. Advanced packaging technologies on the rise
2024: The year when MCUs became AI-enabled
https://www-edn-com.translate.goog/2024-the-year-when-mcus-became-ai-enabled/?fbclid=IwZXh0bgNhZW0CMTEAAR1_fEakArfPtgGZfjd-NiPd_MLBiuHyp9qfiszczOENPGPg38wzl9KOLrQ_aem_rLmf2vF2kjDIFGWzRVZWKw&_x_tr_sl=en&_x_tr_tl=fi&_x_tr_hl=fi&_x_tr_pto=wapp
The AI party in the MCU space started in 2024, and in 2025, it is very likely that there will be more advancements in MCUs using lightweight AI models.
Adoption of AI acceleration features is a big step in the development of microcontrollers. The inclusion of AI features in microcontrollers started in 2024, and it is very likely that in 2025, their features and tools will develop further.
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.
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
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/
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.
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.
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.
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.
For security and compliance leaders, the EU AI Act represents just one piece of a broader AI governance puzzle that will dominate 2025.
The next 12-18 months will require sustained focus and collaboration across security, compliance, and technology teams to stay ahead of these developments.
The Global Partnership on Artificial Intelligence (GPAI) is a multi-stakeholder initiative which aims to bridge the gap between theory and practice on AI by supporting cutting-edge research and applied activities on AI-related priorities.
https://gpai.ai/about/#:~:text=The%20Global%20Partnership%20on%20Artificial,activities%20on%20AI%2Drelated%20priorities.
830 Comments
Tomi Engdahl says:
https://www.schneier.com/blog/archives/2025/02/an-llm-trained-to-create-backdoors-in-code.html
Tomi Engdahl says:
How AI generated code compounds technical debt
“I don’t think I have ever seen so much technical debt being created in such a short period of time”
https://leaddev.com/software-quality/how-ai-generated-code-accelerates-technical-debt
GitClear’s latest report exposes rising code duplication and declining quality as AI coding tools gain in popularity.
It’s never been easier to create code. With today’s LLM-based coding assistants embedded in the Integrated Development Environment (IDE), you can create multi-line code blocks with a single prompt or press of the tab key.
Ever since AI coding tools entered the scene, engineering best practices like the don’t repeat yourself (DRY) principle have been slipping.
“I don’t think I have ever seen so much technical debt being created in such a short period of time during my 35-year career in technology,” says API evangelist Kin Lane, referring to AI-generated code proliferation.
Tomi Engdahl says:
New GPT-4o Copilot code completion model now available for Copilot in JetBrains IDEs
https://github.blog/changelog/2025-02-19-new-gpt-4o-copilot-code-completion-model-now-available-for-copilot-in-jetbrains-ides/
Tomi Engdahl says:
https://dawn.fi/uutiset/2025/02/20/google-gemini-suomeksi-google-workspace?fbclid=IwY2xjawIlcZtleHRuA2FlbQIxMQABHQzV8_HM1lVL4QGdC6tAgEEi44YHta9SfClwGc3nUsnq1Boi6nGCljWxyw_aem_Ly1UX2elzU0hOxouXuZPjw
Tomi Engdahl says:
https://techxplore.com/news/2025-02-indiana-jones-jailbreak-approach-highlights.html
Tomi Engdahl says:
https://www.tivi.fi/uutiset/ilmainen-tekoaly-tulee-taas-kiinasta/e55a5737-4d3f-46bd-8ce9-fd5b4519505a
Baidu tekee Ernie Bot -tekoälystään maksuttoman vastatakseen kilpailuun Kiinan tekoälymarkkinoilla.
Tomi Engdahl says:
https://mobiili.fi/2025/02/18/googlen-tekoalypalvelun-henkilokohtainen-tekoalytutkimusassistentti-deep-research-saatavilla-nyt-myos-gemini-mobiilisovelluksissa/
Tomi Engdahl says:
https://techxplore.com/news/2025-02-darkmind-backdoor-leverages-capabilities-llms.html
Tomi Engdahl says:
”Rikolliset hyödyntävät AI:ta tehostaakseen, automatisoidakseen ja skaalatakseen hyökkäystapojaan”
https://mobiili.fi/2025/02/17/nama-olivat-yleisimmat-haittaohjelmat-tammikuussa-rikolliset-hyodyntavat-aita-tehostaakseen-automatisoidakseen-ja-skaalatakseen-hyokkaystapojaan/
Tomi Engdahl says:
https://www.elementsofai.com/fi/
Tomi Engdahl says:
https://www.eetimes.com/telink-semiconductor-launches-ml-and-ai-tl-edgeai-platform/
Tomi Engdahl says:
As Hype Fades, OpenAI Suddenly Cancels Release of Its Hot Upcoming AI
“We will no longer ship o3 as a standalone model.”
https://futurism.com/openai-o3-release
Tomi Engdahl says:
https://www.marktechpost.com/2025/02/13/can-1b-llm-surpass-405b-llm-optimizing-computation-for-small-llms-to-outperform-larger-models/
Tomi Engdahl says:
AI agent startups: the biggest European funding rounds since the start of 2024
Startups from France, Germany and the UK that dominate the list
https://sifted.eu/articles/ai-agent-funding-rounds
Tomi Engdahl says:
Building Your Own AI Dream Team: No Code, No Problem
https://www.pymnts.com/news/artificial-intelligence/2025/building-your-own-ai-dream-team-no-code/
Artificial intelligence agents can transform a small staff into a productive workforce that can tackle tasks typically handled by larger teams.
While most people are familiar with AI chatbots like ChatGPT, Perplexity AI or Claude, AI agents are the next level for productivity at work. They provide information like chatbots, and they do the task.
They can also manage other AI agents in more complex work.
Companies like Salesforce and ServiceNow, and platforms like Agent.ai, offer AI-powered agents that can support customer service, data management, workflow automation and sales processes. Cloud providers Amazon Web Services, Microsoft Azure and Google Cloud also offer agents on their platforms.
“The impact for business is going to be profound,” David Johnston, adviser to investment firm DLTx, told PYMNTS. “Having expert-level AI available to anyone is going to accelerate all types of work that involve writing, analyzing, designing and digitally creating just about anything,”
Tomi Engdahl says:
https://www.csoonline.com/article/3819176/top-5-ways-attackers-use-generative-ai-to-exploit-your-systems.html
Tomi Engdahl says:
https://github.blog/changelog/2025-02-19-announcing-the-general-availability-of-github-copilot-extensions/
Tomi Engdahl says:
https://www.tivi.fi/uutiset/googlen-tekoaly-teki-vuosien-tutkimustyon-muutamassa-hetkessa/eec5a464-a0b4-4936-9e24-e325c363c3f0
Tomi Engdahl says:
China connects everything to DeepSeek in nationwide plan
Private and state sectors are on board as the new AI is used in chatbots, smart vehicles, government departments and schools
https://asiatimes.com/2025/02/china-connects-everything-to-deepseek-in-nationwide-plan/#
Tomi Engdahl says:
Is AI really thinking and reasoning — or just pretending to?
The best answer — AI has “jagged intelligence” — lies in between hype and skepticism.
https://www.vox.com/future-perfect/400531/ai-reasoning-models-openai-deepseek
Tomi Engdahl says:
Let’s take a step back. What exactly is reasoning, anyway?
AI companies like OpenAI are using the term reasoning to mean that their models break down a problem into smaller problems, which they tackle step by step, ultimately arriving at a better solution as a result.
Tomi Engdahl says:
6 ways GPT Operator is changing PPC automation
GPT Operator isn’t a complete solution. Yet. Here’s where GPT Operator actually works in PPC applications – and where it falls short.
https://searchengineland.com/gpt-operator-changing-ppc-automation-452123
PPC automation has always been about efficiency.
We’ve relied on scripts, rule-based optimizations, and APIs to manage campaigns at scale.
These tools have been essential, but they all share a common limitation: they follow strict, pre-programmed logic.
So people are still needed, even with simple and boring tasks.
But now we’re on the cusp of a new type of automation that can further reduce our workloads and free up our brains for more engaging and strategic work.
GPT Operator, a Computer Using Agent (CUA) from OpenAI can change how we think about automation constraints because it has the power to be more flexible than traditional automation tools.
What is GPT Operator?
This new AI-powered feature allows ChatGPT to browse the web and execute tasks without APIs. Unlike traditional automation, which is rigid and deterministic, GPT Operator can make dynamic decisions on the fly.
Caveat: GPT Operator is only available in the U.S. and requires a subscription to the $200/month Pro plan. So, it isn’t a realistic solution for the majority of marketers today.
But, as with everything in AI, GPT Operator should get cheaper and more widely accessible quickly, so consider this a glimpse into what’s possible in the near future.
Why GPT Operator is exciting for PPC automation
Automation has transformed PPC over the years, but it has always had boundaries.
Rule-based systems work well when conditions are predictable.
A script can lower bids if ROAS drops below a set target or add a negative keyword if a search term spends more than expected without converting.
These deterministic automations ensure consistency, but they limit what can be automated when nuance is needed.
In the world of PPC, which is evolving so quickly, nuanced automation would be a boon.
Search behavior shifts, competitor strategies evolve, and not all decisions can be reduced to a simple if-then statement.
GPT Operator represents a step toward adaptive automation – where AI doesn’t just follow a rule, but adjusts based on changing conditions.
Instead of simply executing a command, GPT Operator can interpret, analyze, and make informed decisions in real time.
But this raises an important question:
Is rule-based automation no longer necessary?
It’s an interesting question, but I believe Zapier and similar deterministic automation tools still serve an important role.
There are two types of processes in PPC: deterministic and non-deterministic. Deterministic processes follow predictable rules and work well when the logic is clear and repeatable. Flexible automation, on the other hand, is needed when tasks require interpretation.
Deterministic automation (scripts, rules, APIs) is reliable, predictable, and efficient but fails when judgment or adaptability is required.
Flexible automation (GenAI, GPT Operator) is context-aware and adaptable, capable of handling unstructured data but slower, requiring monitoring, and doesn’t always get details right.
We’ve always needed both, but flexible automation has been much harder to implement — until now.
Tomi Engdahl says:
https://dsa.si/news/why-intels-bold-moves-could-spark-a-paradigm-shift-in-ai-investments/32265/
Intel Corporation is emerging as a significant player in the AI industry, not just participating but potentially leading the next technological wave.
A strategic restructuring involving Intel’s DesignCo and IFS divisions and TSMC as a major partner could reshape the company’s business landscape.
This potential reorganization positions TSMC to enhance U.S.-based ventures, bolstering its role in advanced foundry services and mitigating tariff issues.
Intel’s focus on x86 technology and AI ambitions may impact competitors like AMD, influencing industry dynamics.
The AI industry is spurring broader discussions on ethics, emphasizing transparency, accountability, and equitable outcomes.
Tomi Engdahl says:
It-alan yritys käynnisti muutosneuvottelut ja nosti samalla esiin tekoälyn – ”Kyse ei ole siitä, että se veisi työpaikkamme”
Aleksi Kolehmainen16.2.202509:03MuutosneuvottelutDigitalous
Siilin mukaan tekoäly ei kokonaisuudessaan vie yhtiön työpaikkoja, mutta se muuttaa työn painopisteitä ja tapoja, joilla työtä tehdään.
https://www.tivi.fi/uutiset/it-alan-yritys-kaynnisti-muutosneuvottelut-ja-nosti-samalla-esiin-tekoalyn-kyse-ei-ole-siita-etta-se-veisi-tyopaikkamme/f24f9243-a157-4200-83a5-8b390f58a2f2
Tomi Engdahl says:
ChatGPT:n kehittäjä julkisti mykistävät luvut
21.2.202519:01
Yksittäisten käyttäjien lisäksi OpenAI:lla on seitsennumeroinen määrä yritysasiakkaita.
https://www.mikrobitti.fi/uutiset/chatgptn-kehittaja-julkisti-mykistavat-luvut/5eb5a7ba-8c05-4ecf-854d-872c45ae4283
Tekoäly-yhtiö OpenAI:lla on helmikuussa ollut yli 400 miljoonaa viikottaista käyttäjää. Palvelun edustaja kertoi asiasta uutistoimisto Reutersille torstaina. Käytännössä luku luultavasti koostuu lähinnä ChatGPT:n käyttäjistä.
Käyttäjien määrä on kasvanut varsin nopeasti. Vielä joulukuussa viikottaisia käyttäjiä oli vain 300 miljoonaa, mikä sekin on toki todella paljon.
Kasvu ei näytä taittuneen edes siihen, kun kiinalainen Deepseekin saapui tekoälypiireihin tammikuun lopulla.
Deepseek tosin haukkasi ainakin Yhdysvalloissa isosti paikallisten tekoäly- ja tietotekniikkayritysten arvoa pörssissä. OpenAI:ta on tukenut voimakkaasti Microsoft, jonka osakkeiden arvo putosi Deepseekin ansiosta Nasdaq-pörssissä 2,1 prosenttia, Reuters kertoi tammikuun lopulla.
400 miljoonan viikottaisen käyttäjän lisäksi OpenAI:lla on nykyään kaksi miljoonaa yritysasiakasta.
Yrityskäyttäjät maksavat OpenAI:n palveluiden käytöstä, eli kasvu näkyy OpenAI:lla oletettavasti myös merkittävänä ansioiden lisäyksenä.
Tomi Engdahl says:
Yksi USA:n suurimmista lehdistä alkaa käyttää tekoälyä
18.2.202512:38|päivitetty18.2.202514:01
Lehdessä on varsin kattavat ohjeet siitä, mitä tekoälyllä saa ja ei saa toimituksessa tehdä.
https://www.mikrobitti.fi/uutiset/yksi-usan-suurimmista-lehdista-alkaa-kayttaa-tekoalya/6551c9b4-544f-4e0d-9128-5c5e9f05408d
Yhdysvaltain tilatuimpiin sanomalehtiin lukeutuva The New York Times (NYT) aikoo alkaa hyödyntää tekoälyä toimituksessaan.
Ihmistoimittajia ei olla kuitenkaan korvaamassa tekoälyllä, vaan uudistus vain tuo heidän käyttöönsä uusia tehokkaampia työskentelymenetelmiä. Tämä erottaa NYT:n esimerkiksi Cnetin, Gizmodon ja Quartzin vastaavista hankkeista, joissa on julkaistu täysin tekoälyn kirjoittamia artikkeleita.
Asia selviää verkkolehti Semaforin käsiinsä saamista tiedoista. Sen mukaan lehden työntekijöille on jaeltu ohjeita tekoälytyökalujen käyttöön niin tekstinä kuin videollakin.
New York Times goes all-in on internal AI tools
https://www.semafor.com/article/02/16/2025/new-york-times-goes-all-in-on-internal-ai-tools
The New York Times is greenlighting the use of AI for its product and editorial staff, saying that internal tools could eventually write social copy, SEO headlines, and some code.
In messages to newsroom staff, the company announced that it’s opening up AI training to the newsroom, and debuting a new internal AI tool called Echo to staff, Semafor has learned. The Times also shared documents and videos laying out editorial do’s and don’t for using AI, and shared a suite of AI products that staff could now use to develop web products and editorial ideas.
“Generative AI can assist our journalists in uncovering the truth and helping more people understand the world. Machine learning already helps us report stories we couldn’t otherwise, and generative AI has the potential to bolster our journalistic capabilities even more,” the company’s editorial guidelines said.
“Likewise, the Times will become more accessible to more people through features like digitally voice[d] articles, translations into other languages, and uses of generative AI we have yet to discover. We view the technology not as some magical solution but as a powerful tool that, like many technological advances before, may be used in service of our mission.”
The company said it was approving a number of AI programs for editorial and product staff, including GitHub Copilot programming assistant for coding, Google’s Vertex AI for product development, NotebookLM, the NYT’s ChatExplorer, some Amazon AI products, and OpenAI’s non-ChatGPT API through the New York Times’ business account (only with approval from the company’s legal department). The Times also announced it had built Echo, an in-house beta summarization tool to allow journalists to condense Times articles, briefings, and interactives.
The paper encouraged editorial staff to use these AI tools to generate SEO headlines, summaries, and audience promos; suggest edits; brainstorm questions and ideas and ask questions about reporters’ own documents; engage in research; and analyze the Times’ own documents and images. In a training video shared with staff, the Times suggested using AI to come up with questions to ask the CEO of a startup during an interview. Times guidelines also said it could use AI to develop news quizzes, social copy, quote cards, and FAQs.
In a series of training documents, editorial guidelines laid out possible use cases for journalists, including prompts such as:
How many times was Al mentioned in these episodes of Hard Fork?
Can you revise this paragraph to make it tighter?
Pretend you are posting this Times article to Facebook. How would you promote it?
Summarize this Times article in a concise, conversational voice for a newsletter.
Can you propose five search-optimized headlines for this Times article?
Can you summarize this play written by Shakespeare?
Can you summarize this federal government report in layman’s terms?
Still, the company has bracketed its AI use, noting the potential risks for copyright infringement and exposure of sources.
The company told editorial staff they should not use AI to draft or significantly revise an article, input third party copyrighted materials (particularly confidential source information), use AI to circumvent a paywall, or publish machine-generated images or videos, except to demonstrate the technology and with proper labeling. The company said some unapproved AI tools, if used improperly, could waive the Times’ right to protect sources and notes.
Tomi Engdahl says:
Why China’s approach to AI intrigues Switzerland
https://www.swissinfo.ch/eng/science/why-chinas-approach-to-ai-intrigues-switzerland/88870403
Beijing’s strict rules on the use of artificial intelligence established a first-of-its-kind regulatory system. Now Switzerland is looking with interest at China as it aims to become a bridge between East and West in the global AI race.
From grocery shopping to hospitals with robots among the doctorsExternal link, artificial intelligence (AI) is an integral part of daily life in China.
“When I leave my house in the morning, everything is on my smartphone,” says Philippe Roesle, who has headed Swissnex, the Swiss research and innovation outpost in Shanghai, since 2022. In China, AI-powered facial recognition apps and systems give access to homes, metro stations, and even public toiletsExternal link.
China is not only adopting AI on a large scale but is also challenging the US in the development of advanced systems. The recent launch of the powerful and efficient Chinese generative AI model DeepSeek has called US leadership in the field into question.
Rules around AI give China an edge
China’s system of regulations gives it an advantage in the race to dominate AI, says Bhaskar Chakravorti, a technology expert at the Fletcher School of Tufts University (US).
“China has always focused on regulation to maintain state control,”
ensuring that technology aligns with government priorities. This tight control has also allowed China to outpace the US in setting ethical and regulatory frameworks.
This is important to guide development and make systems safe from misuse, bias, and cyber threats while enhancing reliability. “Strong AI development is not enough to win users’ trust – clear rules are also necessary,”
Switzerland has understood well the importance of common rules on AI. The Alpine country wants to leverage its neutrality, its technology and its diplomatic skills to mediate between East and West in the AI race and guarantee global ethical and regulatory standards.
“We need to understand how China thinks,” says Roesle. “Closing the door on Beijing would be unproductive.”
China: AI regulation pioneer
Understanding the Chinese mentality is not so difficult, says Guangyu Qiao-Franco, an assistant professor and expert on AI and China at the Dutch Radboud University: Beijing and the West “share many values” in their approach to AI, including human-centricity, privacy protection and non-discrimination. In 2017, anticipating the European Union (EU), China introduced its first ethical guidelinesExternal link on the responsible use of AI, later consolidated in 2021External link.
These rules require AI systems to be fair, avoid bias and data leaks, and prevent social instability.
“China is the only country that has specific rules on algorithms and how they should be used in everyday life,” says Junhua Zhu, a researcher in AI ethics and governance at the University of Turku, Finland.
In contrast, the US still lacks meaningful AI regulations more than two years after the launch of ChatGPT. The EU’s AI Act, which came into force in 2024, does not require prior scrutiny of AI models like China does. And Switzerland is lagging in establishing a regulatory framework for AI, which should arrive by the end of 2026, according to a recent government announcementExternal link.
“China is leading the way,”
State control of AI benefits China at the expense of ethics
To prevent the spread of narratives that could undermine the Party’s legitimacy, China requires AI-generated content to reflect the “core values of socialism” and bans content inciting separatism or terrorism.
Despite citing privacy in its ethics guidelines, the Chinese government has access to the largest amount of data on its citizens of any country in the world. “There is no data protection like in Europe. It is the Wild West,” L’Orange says. This enables rapid AI development, while many democratic countries face rigid regulatory constraints related to privacy.
She finds “frustrating” the stereotypical image of China as a country without ethics where AI is regarded as a mere tool for mass surveillance. In her view, Chinese culture puts collective good over individual freedoms, which is why the population widely accepts AI surveillance. “These technologies are largely perceived as tools for ensuring national security and public stability,” she explains, calling the Chinese system “a democracy that differs from Western models”.
Rongsheng Zhu, a researcher at Tsinghua University in Beijing, also criticises the foreign narrative on Chinese AI and defends China’s strict control over AI systems developed by private companies. This, he says, is how the government protects citizens’ rights.
“If for democracies like the US this means violating the free enterprise, then I prefer the actions of my government,” adds Zhu.
Pulver of the CSS in Zurich also doubts that Switzerland can maintain a neutral approach and emphasises the country’s commercial dependence on China and the US. Switzerland has signed a privileged free trade agreement with Beijing, while it depends on US chips for AI development.
Tomi Engdahl says:
OpenAI laajensi käyttäjän puolesta tehtäviä suorittavan Operator-tekoälyagenttinsa saatavuutta – EU:ssa joudutaan yhä odottamaan
https://mobiili.fi/2025/02/21/openai-laajensi-kayttajan-puolesta-tehtavia-suorittavan-operator-tekoalyagenttinsa-saatavuutta-eussa-joudutaan-yha-odottamaan/
Tekoäly-yhtiö OpenAI on laajentanut tammikuussa julkistetun Operator-tekoälyagenttinsa saatavuutta. Valitettavasti Euroopan unionissa joudutaan yhä odottamaan.
OpenAI julkaisi Operatorin aluksi Yhdysvalloissa tammikuussa. Nyt saatavuus on laajentunut useimpiin maihin, joissa ChatGPT on saatavilla, mukaan lukien Australia, Brasilia, Etelä-Korea, Intia, Iso-Britannia, Japani, Kanada ja Singapore.
Valitettavasti Euroopan unionissa Operatoria ei ole vielä julkaistu.
Operator vaatii toistaiseksi alkaen 200 dollaria kuukaudessa maksavan ChatGPT Pro -tilauksen. Myöhemmin Operator on tarkoitus tuoda myös osaksi Plus-, Team- ja Enterprise-tilauksia.
ChatGPT-palvelua laajentava Operator voi suorittaa monimutkaisia tehtäviä käyttäjänsä puolesta.
Operatorin voi valtuuttaa hoitamaan puolestaan monenlaisia tehtäviä verkossa täysin automaattisesti, OpenAI kuvailee. Sille on vain tekstillä kuvailtava, mitä halutaan, minkä jälkeen sen tulisi selvitä omillaan.
Operator perustuu kehittyneeseen GPT-4o-kielimalliin sekä konenäköön kyeten täten tarkastelemaan verkkosivuja ja käyttämään niitä ”kaikilla hiiren ja näppäimistön sallimilla tavoilla”. Käytännössä se voi siis esimerkiksi selailla, klikkailla ja tehdä verkko-ostoksia käyttäjänsä puolesta.
OpenAI:n mukaan Operator on suunniteltu jättämään huomiotta ”vahingolliset pyynnöt ja kielletyt sisällöt”. Lisäksi se pyytää käyttäjältään apua jumiin jäädessään sekä aina, kun sivustolle on syötettävä kirjautumistunnusten kaltaisia tietoja. Lisäksi sen ”pitäisi” varmistaa käyttäjän suostumus sähköposteja lähettäessään.
Monet Pohjois-Amerikassa suositut verkkokaupat ja sivustot, kuten DoorDash, Instacart, OpenTable ja Uber ovat auttaneet OpenAI:ta Operatorin kehittämisessä. Näin on haluttu varmistaa, että avustaja soveltuu ”tosielämän tilanteisiin kunnioittaen kuitenkin vakiintuneita toimintatapoja”
Tomi Engdahl says:
Tekoälyagentit: Uusi työkaveri vai pelkkä hype?
https://www.advania.fi/blogi/tekoalyagentit-uusi-tyokaveri-vai-pelkka-hype
yksi teema tuntui erottautuvan selkeästi joukosta. Syksyn kuumimpia puheenaiheita onkin, miten tekoälyagentit tulevat muuttamaan työskentelytapoja tulevaisuudessa.
Moni saattaa miettiä, mitä agentit oikeastaan ovat tai mitä niillä oikeasti voi tehdä. Tässä blogissa käyn läpi, mitä tekoälyagentit ovat ja miten organisaatiot voivat hyödyntää niitä työnteon tehostamisessa – vaikka heti.
Mitä agentit ovat?
Nykyisten tekoälysovellusten haasteena on usein niiden yleisluontoisuus, eli ”geneerisyys”. Laajat kielimallit eivät aina yksinään ratkaise liiketoiminnan haasteita, koska niiltä puuttuu kyky syventyä aiheeseen juuri halutulla tavalla. Voisi sanoa, että yleiset tekoälypalvelut, kuten ChatGPT, ovat kuin monitoimityökaluja. Ne voivat venyä moniin eri tehtäviin, mutta joskus tulokset saattavat vaihdella. Joissain tilanteissa ne eivät toimi ollenkaan.
Agenteilla on mahdollisuus luoda täsmäratkaisu, joka vastaa luotettavasti organisaation tarpeisiin. Yksinään agentti on rajallinen työkalu, mutta useampi agentti yhdessä voi muodostaa tehokkaan työkalupakin.
Teknisesti ajateltuna agentti on kolme eri tekoälykonseptia yhdistettynä: työntekijä (kielimallit), työvälineet (Pluginit + Connectorit) ja annetut ohjeistukset (Promptaus / Fine-tuning), joiden perusteella haluttu toimeksianto saadaan tehtyä. Dataa voidaan tuoda kielimallille eri tavoin, mutta ilman oikeita ohjeistuksia ja työvälineitä edes hyvä data ei riitä. Siksi tiettyyn tarkoitukseen kohdistetut agentit ovat tehokkaampia ja voivat suoriutua paremmin vaikeammistakin tehtävistä.
Esimerkki tekoälyagentista
Yksinkertaisimmat agentit ovat sellaisia, jotka on sidottu tiettyyn dataan ja osaavat hakea tietoa siitä. Kun agentit yhdistetään tietovarastoihin, niille voidaan kertoa, missä muodossa tieto tulee ja miten sitä kannattaa käsitellä. Esimerkkinä voisi olla intra-agentti, joka tuntee yrityksen intranetin sisällön ja osaa vastata siihen liittyviin kysymyksiin. Ohjeistuksilla voidaan myös päättää, miten agenttien kannattaisi esittää tietoa; esimerkiksi IT-tukeen erikoistunut agentti voisi antaa teknisiä neuvoja käyttäjille yksinkertaisemmassa muodossa, vaihe vaiheelta.
Agentit eivät kuitenkaan ole pelkästään perinteisiä tiedonhaku- tai neuvontatyökaluja. On myös mahdollista luoda agentteja, jotka voivat hyödyntää automaatioita tai yhteyksiä muihin järjestelmiin, jotta normaalisti työläistä prosesseista tulisi käyttäjäystävällisempiä. Jatkumona aiemmin mainitulle IT-tuen agentille voisi olla ominaisuus, joka lähettää viestin tai avaa tiketin IT-asiantuntijalle, jos tekoälyn ohjeista ei löydy ratkaisua käyttäjän ongelmaan.
Tällainen agentti voisi ymmärtää syvällisesti organisaation käyttämät tikettijärjestelmät ja osaisi käsitellä niihin tarvittavaa dataa. Käyttäjän ei tarvitsisi täytellä lomakkeita tai avata uusia sovelluksia, vaan riittäisi, että hän juttelee agentin kanssa normaalisti, ja agentti hoitaisi loput.
Agenttien käyttöönotossa on hyvä miettiä, miten ne toimivat yhdessä. Joskus yksi agentti riittää, mutta usein tarvitaan useamman agentin tiimityötä homman hoitamiseksi. Agentit voivat muodostaa tehokkaan ryhmän, joka osaa auttaa käyttäjää monenlaisissa ongelmissa. Käyttäjä kertoo ongelman, jonka agentit käyvät yhdessä läpi parhaan ratkaisun tarjoamiseksi käyttäjälle.
Käyttäjä ei välttämättä edes huomaa, että häntä auttaa useampi agentti.
Vaikka agentteja voikin ajatella uutena työkaverina, on tärkeä muistaa, että ne ovat vain työkaluja ihmisten työn helpottamiseksi. Tekoäly ei aina pysty hoitamaan kaikkea itse, joten käyttäjien on hyvä olla prosessissa mukana. Vaikka agentti täyttäisikin tukipyyntölomakkeen käyttäjän puolesta, on hyvä näyttää tiedot käyttäjälle ja pyytää hyväksyntä, että kaikki on kunnossa. Näin käyttäjä säilyttää kontrollin datasta.
Agenttien nykypäivä
Agentteja siis voidaan ajatella seuraavana askeleena tekoälyn jalostamisessa, mutta miten agentteja on jo käytössä nykyaikana?
Advania AI Hub on Advanian kehittämä tekoälyalusta, joka mahdollistaa uusien tekoälyagenttien luomisen ja käytön vaivattomasti. AI Hub perustuu Microsoftin avoimen lähdekoodin Semantic Kernel -arkkitehtuuriin, mikä mahdollistaa nopean kehityksen yrityksen erityistarpeiden mukaisesti.
Agentit ovat myös tulleet mukaan Microsoft 365 Copilotiin. Copilot-agenttien avulla Microsoft 365 Copilot voidaan yhdistää uusiin tietojärjestelmiin sekä automaatioihin tehostamaan yrityksen toimintaa. Käyttäjät voivat myös luoda itselleen juuri omaa työtä tehostavia agentteja käyttöliittymästä käsin.
Tomi Engdahl says:
Gartnerin teknologiatrendit 2025 – energiatehokas tietojenkäsittely – tekoälyn energiankulutus ja sen hallinta
https://www.exove.com/fi/blogit/gartnerin-teknologiatrendit-2025-energiatehokas-tietojenkasittely-tekoalyn-energiankulutus-ja-sen-hallinta/