Today, we’re launching NextGenAI, a first-of-its-kind consortium with 15 leading research institutions dedicated to using AI to accelerate research breakthroughs and transform education.
AI has the power to drive progress in research and education—but only when people have the right tools to harness it. That’s why OpenAI is committing $50M in research grants, compute funding, and API access to support students, educators, and researchers advancing the frontiers of knowledge.
Uniting institutions across the U.S. and abroad, NextGenAI aims to catalyze progress at a rate faster than any one institution would alone. This initiative is built not only to fuel the next generation of discoveries, but also to prepare the next generation to shape AI’s future.
“My goal isn’t to make him a generative AI wizard,” White said. “It’s to give him a foundation for using AI to be creative, build, explore perspectives and enrich his learning.”
White is part of a growing number of parents teaching their young children how to use AI chatbots so they are prepared to deploy the tools responsibly as personal assistants for school, work and daily life when they’re older.
We introduce AI co-scientist, a multi-agent AI system built with Gemini 2.0 as a virtual scientific collaborator to help scientists generate novel hypotheses and research proposals, and to accelerate the clock speed of scientific and biomedical discoveries.
There is a speed limit. GenAI technology continues to advance at incredible speed. However, most organizations are moving at the speed of organizations, not at the speed of technology. No matter how quickly the technology advances—or how hard the companies producing GenAI technology push—organizational change in an enterprise can only happen so fast.
Barriers are evolving. Significant barriers to scaling and value creation are still widespread across key areas. And, over the past year regulatory uncertainty and risk management have risen in organizations’ lists of concerns to address. Also, levels of trust in GenAI are still moderate for the majority of organizations. Even so, with increased customization and accuracy of models—combined with a focus on better governance— adoption of GenAI is becoming more established.
Some uses are outpacing others. Application of GenAI is further along in some business areas than in others in terms of integration, return on investment (ROI) and expectations. The IT function is most mature; cybersecurity, operations, marketing and customer service are also showing strong adoption and results. Organizations reporting higher ROI for their most scaled initiatives are broadly further along in their GenAI journeys.
One finding from our student survey that stood out to us: Many college and university students are teaching themselves and their friends about AI without waiting for their institutions to provide formal AI education or clear policies about the technology’s use. The education ecosystem is in an important moment of exploration and learning, but the rapid adoption by students across the country who haven’t received formalized instruction in how and when to use the technology creates disparities in AI access and knowledge.
The enclosed snapshot of how young people are using ChatGPT provides insight into the state of AI use among America’s college-aged students. We also include actionable proposals to help address adoption gaps. We hope these insights and proposals can inform research and policy conversation across the nation’s education ecosystem about how to achieve outcomes that support our students, our workforce, and the economy. By improving literacy, expanding access, and implementing clear policies, policymakers and educators can better integrate AI into our educational infrastructure and ensure that our workforce is ready to both sustain and benefit from our future with AI.
The California State University system has partnered with OpenAI to launch the largest deployment of AI in higher education to date.
The CSU system, which serves nearly 500,000 students across 23 campuses, has announced plans to integrate ChatGPT Edu, an education-focused version of OpenAI’s chatbot, into its curriculum and operations. The rollout, which includes tens of thousands of faculty and staff, represents the most significant AI deployment within a single educational institution globally.
We’re still in the early stages of AI adoption in education, and it is critical that the entire ecosystem—education systems, technologists, educators, and governments—work together to ensure that all students globally have access to AI and develop the skills to use it responsibly
Leah Belsky, VP and general manager of education at OpenAI.
As you read through these use cases, you’ll notice that each one addresses multiple tasks from our list above.
1. Researching a topic for a lesson
2. Creating Tasks For Practice
3. Creating Sample Answers
4. Generating Ideas
5. Designing Lesson Plans
6. Creating Tests
7. Using AI in Virtual Classrooms
8. Creating Images
9. Creating worksheets
10. Correcting and Feedback
Introducing deep research — from openai.com An agent that uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you. Available to Pro users today, Plus and Team next.
[On 2/2/25 we launched] deep research in ChatGPT, a new agentic capability that conducts multi-step research on the internet for complex tasks. It accomplishes in tens of minutes what would take a human many hours.
Deep research is OpenAI’s next agent that can do work for you independently—you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst.
Comments/information per The Rundown AI: The Rundown: OpenAI just launchedDeep Research, a new ChatGPT feature that conducts extensive web research on complex topics and delivers detailed reports with citations in under 30 minutes.
The details:
The system uses a specialized version of o3 to analyze text, images, and PDFs across multiple sources, producing comprehensive research summaries.
Initial access is limited to Pro subscribers ($200/mo) with 100 queries/month, but if safety metrics remain stable, it will expand to Plus and Team users within weeks.
Research tasks take between 5-30 minutes to complete, with users receiving a list of clarifying questions to start and notifications when results are ready.
Deep Research achieved a 26.6% on Humanity’s Last Exam, significantly outperforming other AI models like Gemini Thinking (6.2%) and GPT-4o (3.3%).
Why it matters: ChatGPT excels at quick, instant answers, but Deep Research represents the first major consumer attempt at tackling complex tasks that take humans days. Combined with the release of Operator, the landscape is shifting towards longer thinking with autonomous actions — and better results to show for it.
The quality of citations are also genuinely advance. Unlike traditional AI-generated sources prone to hallucinations, Deep Research provides legitimate academic references. Clicking a citation often takes users directly to the relevant highlighted text.
In a demo, the agent generated a comprehensive report on iOS and Android app market trends, showcasing its ability to tackle intricate subjects with accuracy.
Which links to and discusses Andrej Karpathy’s video at:
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This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their “psychology”, and how to get the best use them in practical applications. I have one “Intro to LLMs” video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version.
Introducing Operator — from openai.com A research preview of an agent that can use its own browser to perform tasks for you. Available to Pro users in the U.S.
Today we’re releasing Operator, an agent that can go to the web to perform tasks for you. Using its own browser, it can look at a webpage and interact with it by typing, clicking, and scrolling. It is currently a research preview, meaning it has limitations and will evolve based on user feedback. Operator is one of our first agents, which are AIs capable of doing work for you independently—you give it a task and it will execute it.
Per the Rundown AI:
“OpenAI just launched Operator, an AI agent that can independently navigate web browsers to complete everyday tasks — marking the company’s first major step into autonomous AI assistants.”
I got early access to ChatGPT Operator.
It’s OpenAI’s new AI agent that autonomously takes action across the web on your behalf.
The 9 most impressive use cases I’ve tried (videos sped up):
Assistant uses reasoning, search, and apps to help with daily tasks ranging from simple questions to multi-app actions. You can book dinner, find a forgotten song, call a ride, draft emails, set reminders, and more.
DeepSeek is an advanced AI platform developed by a Chinese startup, offering tools like DeepSeek-R1 (nicknamed “DeepThink”) that rival top models like ChatGPT. Here’s what you need to know:
Key Features
Human-Like Reasoning
Cost-Effective & Open-Source
Web Search Integration
State of AI in 2025 exposed — from theneurondaily.com by Grant Harvey PLUS: When to use Gemini instead of ChatGPT…
The State of AI Development in 2025…
Late last year, we helped Vellum survey over 1,250 AI builders to understand where AI development is really heading. Spoiler alert: It’s not quite the AI takeover you might expect.
Here’s the surprising truth about AI development in 2025: most companies are still figuring it out.
Only 25.1% of businesses have actually deployed AI in production. Everyone else is split between building proofs of concept (21%), beta testing (14.1%), or still working on their strategy (25%). The rest are somewhere between talking to users and evaluating their initial attempts.
DeepSeek hits the scene — MUCH too early to say how this open-source platform will play out here in the United States. Things are tense between the U.S. and Chian.
Over the last week, pretty much everyone in the AI space has been losing their minds over Deepseek R1. The open source community has been loving it, the closed source tech giants have been less than loving it, and even the mainstream media is starting to pick up on how last week’s R1 launch was a big deal
We’ve been trying to understand just how powerful R1 really is, so we rounded up everything we could find that shows off just what this little AI side project can do.
Here’s some WILD demos of what people have done with Deepseek R1 so far:
Deepseek R1 is one of the most amazing and impressive breakthroughs I’ve ever seen — and as open source, a profound gift to the world. ??
Is DeepSeek the new DeepMind? — from ai-supremacy.com by Michael Spencer AI supremacy isn’t just about compute or U.S. leadership, it’s about how you work to make models more efficient and improve their accessibility for everyone.
Over the last week especially but over the last month generally, the AI Zeitgeist is flooding with what DeepSeek’s R1 means for the larger ecosystem and the future of AI as a whole. See some articles I’m reading on DeepSeek here (Google Doc).
It’s an important moment in so far as everything from export controls to AI Infrastructure, to capex spend or AI talent moats are being put into question.
The following AI capabilities will start rolling out to Google Workspace Business customers today and to Enterprise customers later this month:
Get AI assistance in Gmail, Docs, Sheets, Meet, Chat, Vids, and more: Do your best work faster with AI embedded in the tools you use every day.Gemini streamlines your communications by helping you summarize, draft, and find information in your emails, chats, and files. It can be a thought partner and source of inspiration, helping you create professional documents, slides, spreadsheets, and videos from scratch. Gemini can even improve your meetings by taking notes, enhancing your audio and video, and catching you up on the conversation if you join late.
Chat with Gemini Advanced, Google’s next-gen AI: Kickstart learning, brainstorming, and planning with the Gemini app on your laptop or mobile device. Gemini Advanced can help you tackle complex projects including coding, research, and data analysis and lets you build Gems, your team of AI experts to help with repeatable or specialized tasks.
Unlock the power of NotebookLM Plus: We’re bringing the revolutionary AI research assistant to every employee, to help them make sense of complex topics. Upload sources to get instant insights and Audio Overviews, then share customized notebooks with the team to accelerate their learning and onboarding.
Google’s Gemini AI is stepping up its game in Google Workspace, bringing powerful new capabilities to your favorite tools like Gmail, Docs, and Sheets:
AI-Powered Summaries: Get concise, AI-generated summaries of long emails and documents so you can focus on what matters most.
Smart Reply: Gemini now offers context-aware email replies that feel more natural and tailored to your style.
Slides and images generation: Gemini in Slides can help you generate new images, summarize your slides, write and rewrite content, and refer to existing Drive files and/or emails.
Automated Data Insights: In Google Sheets, Gemini helps create a task tracker, conference agenda, spot trends, suggest formulas, and even build charts with simple prompts.
Intelligent Drafting: Google Docs now gets a creativity boost, helping you draft reports, proposals, or blog posts with AI suggestions and outlines.
Meeting Assistance: Say goodbye to the awkward AI attendees to help you take notes, now Gemini can natively do that for you – no interruption, no avatar, and no extra attendee. Meet can now also automatically generate captions to lower the language barrier.
Eveyln (from FlexOS) also mentions that CoPilot is getting enhancements too:
It’s exactly what we predicted: stand-alone AI apps like note-takers and image generators have had their moment, but as the tech giants step in, they’re bringing these features directly into their ecosystems, making them harder to ignore.
The Stargate Project is a new company which intends to invest $500 billion over the next four years building new AI infrastructure for OpenAI in the United States. We will begin deploying $100 billion immediately. This infrastructure will secure American leadership in AI, create hundreds of thousands of American jobs, and generate massive economic benefit for the entire world. This project will not only support the re-industrialization of the United States but also provide a strategic capability to protect the national security of America and its allies.
The initial equity funders in Stargate are SoftBank, OpenAI, Oracle, and MGX. SoftBank and OpenAI are the lead partners for Stargate, with SoftBank having financial responsibility and OpenAI having operational responsibility. Masayoshi Son will be the chairman.
Arm, Microsoft, NVIDIA, Oracle, and OpenAI are the key initial technology partners. The buildout is currently underway, starting in Texas, and we are evaluating potential sites across the country for more campuses as we finalize definitive agreements.
Adobe is launching new generative AI tools that can automate labor-intensive production tasks like editing large batches of images and translating video presentations. The most notable is “Firefly Bulk Create,” an app that allows users to quickly resize up to 10,000 images or replace all of their backgrounds in a single click instead of tediously editing each picture individually.
Today we’re rolling out a beta version of tasks—a new way to ask ChatGPT to do things for you at a future time.
Whether it’s one-time reminders or recurring actions, tell ChatGPT what you need and when, and it will automatically take care of it. pic.twitter.com/7lgvsPehHv
OpenAI is launching a new beta feature in ChatGPT called Tasks that lets users schedule future actions and reminders.
The feature, which is rolling out to Plus, Team, and Pro subscribers starting today, is an attempt to make the chatbot into something closer to a traditional digital assistant — think Google Assistant or Siri but with ChatGPT’s more advanced language capabilities.
The Rundown: OpenAI is rolling out Tasks, a new ChatGPT beta feature that allows users to schedule reminders and recurring actions, marking the company’s first step into agentic AI capabilities.
… Why it matters: While reminders aren’t groundbreaking, Tasks lays the groundwork for incorporating agentic abilities into ChatGPT, which will likely gain value once integrated with other features like tool or computer use. With ‘Operator’ also rumored to be coming this month, all signs are pointing towards 2025 being the year of the AI agent.
Top AI Tools of 2024 — from ai-supremacy.com by Michael Spencer (behind a paywall) Which AI tools stood out for me in 2024? My list.
Memorable AI Tools of 2024
Catergories included:
Useful
Popular
Captures the zeighest of AI product innovation
Fun to try
Personally satisfying
NotebookLM
Perplexity
Claude
…
New “best” AI tool? Really? — from theneurondaily.com by Noah and Grant
PLUS: A free workaround to the “best” new AI…
What is Google’s Deep Research tool, and is it really “the best” AI research tool out there? … Here’s how it works: Think of Deep Research as a research team that can simultaneously analyze 50+ websites, compile findings, and create comprehensive reports—complete with citations.
Unlike asking ChatGPT to research for you, Deep Research shows you its research plan before executing, letting you edit the approach to get exactly what you need.
…
It’s currently free for the first month (though it’ll eventually be $20/month) when bundled with Gemini Advanced. Then again, Perplexity is always free…just saying.
We couldn’t just take J-Cal’s word for it, so we rounded up some other takes:
Our take: We then compared Perplexity, ChatGPT Search, and Deep Research (which we’re calling DR, or “The Docta” for short) on robot capabilities from CES revealed:
An excerpt from today’s Morning Edition from Bloomberg
Global banks will cut as many as 200,000 jobs in the next three to five years—a net 3% of the workforce—as AI takes on more tasks, according to a Bloomberg Intelligence survey. Back, middle office and operations are most at risk. A reminder that Citi said last year that AI is likely to replace more jobs in banking than in any other sector. JPMorgan had a more optimistic view (from an employee perspective, at any rate), saying its AI rollout has augmented, not replaced, jobs so far.
Ever since a new revolutionary version of chat ChatGPT became operable in late 2022, educators have faced several complex challenges as they learn how to navigate artificial intelligence systems.
…
Education Week produced a significant amount of coverage in 2024 exploring these and other critical questions involving the understanding and use of AI.
Here are the five most popular stories that Education Week published in 2024 about AI in schools.
Dr. Lodge said there are five key areas the higher education sector needs to address to adapt to the use of AI:
1. Teach ‘people’ skills as well as tech skills
2. Help all students use new tech
3. Prepare students for the jobs of the future
4. Learn to make sense of complex information
5. Universities to lead the tech change
Checking the Pulse: The Impact of AI on Everyday Lives So, what exactly did our users have to say about how AI transformed their lives this year? .
Top 2024 Developments in AI
Video Generation…
AI Employees…
Open Source Advancements…
Getting ready for 2025: your AI team members (Gift lesson 3/3) — from flexos.com by Daan van Rossum
And that’s why today, I’ll tell you exactly which AI tools I’ve recommended for the top 5 use cases to almost 200 business leaders who took the Lead with AI course.
1. Email Management: Simplifying Communication with AI
Microsoft Copilot for Outlook. …
Gemini AI for Gmail. …
Grammarly. …
2. Meeting Management: Maximize Your Time
Otter.ai. …
Copilot for Microsoft Teams. …
Other AI Meeting Assistants. Zoom AI Companion, Granola, and Fathom
3. Research: Streamlining Information Gathering
ChatGPT. …
Perplexity. …
Consensus. …
…plus several more items and tools that were mentioned by Daan.
“I mean, that’s what I’ll always want for my own children and, frankly, for anyone’s children,” Khan said. “And the hope here is that we can use artificial intelligence and other technologies to amplify what a teacher can do so they can spend more time standing next to a student, figuring them out, having a person-to-person connection.”
…
“After a week you start to realize, like, how you can use it,” Brockman said. “That’s been one of the really important things about working with Sal and his team, to really figure out what’s the right way to sort of bring this to parents and to teachers and to classrooms and to do that in a way…so that the students really learn and aren’t just, you know, asking for the answers and that the parents can have oversight and the teachers can be involved in that process.”
More than 100 colleges and high schools are turning to a new AI tool called Nectir, allowing teachers to create a personalized learning partner that’s trained on their syllabi, textbooks, and assignments to help students with anything from questions related to their coursework to essay writing assistance and even future career guidance.
…
With Nectir, teachers can create an AI assistant tailored to their specific needs, whether for a single class, a department, or the entire campus. There are various personalization options available, enabling teachers to establish clear boundaries for the AI’s interactions, such as programming the assistant to assist only with certain subjects or responding in a way that aligns with their teaching style.
“It’ll really be that customized learning partner. Every single conversation that a student has with any of their assistants will then be fed into that student profile for them to be able to see based on what the AI thinks, what should I be doing next, not only in my educational journey, but in my career journey,” Ghai said.
How Will AI Influence Higher Ed in 2025? — from insidehighered.com by Kathryn Palmer No one knows for sure, but Inside Higher Ed asked seven experts for their predictions.
As the technology continues to evolve at a rapid pace, no one knows for sure how AI will influence higher education in 2025. But several experts offered Inside Higher Ed their predictions—and some guidance—for how colleges and universities will have to navigate AI’s potential in the new year.
In the short term, A.I. will help teachers create lesson plans, find illustrative examples and generate quizzes tailored to each student. Customized problem sets will serve as tools to combat cheating while A.I. provides instant feedback.
…
In the longer term, it’s possible to imagine a world where A.I. can ingest rich learner data and create personalized learning paths for students, all within a curriculum established by the teacher. Teachers can continue to be deeply involved in fostering student discussions, guiding group projects and engaging their students, while A.I. handles grading and uses the Socratic method to help students discover answers on their own. Teachers provide encouragement and one-on-one support when needed, using their newfound availability to give students some extra care.
Let’s be clear: A.I. will never replace the human touch that is so vital to education. No algorithm can replicate the empathy, creativity and passion a teacher brings to the classroom. But A.I. can certainly amplify those qualities. It can be our co-pilot, our chief of staff helping us extend our reach and improve our effectiveness.
Today, I want to reflect on two recent OpenAI developments that highlight this evolution: their belated publication of advice for students on integrating AI into writing workflows, and last week’s launch of the full GPTo1 Pro version. When OpenAI released their student writing guide, there were plenty of snarky comments about how this guidance arrives almost a year after they thoroughly disrupted the educational landscape. Fair enough – I took my own side swipes initially. But let’s look at what they’re actually advising, because the details matter more than the timing.
Tutoring programs exploded in the last five years as states and school districts searched for ways to counter plummeting achievement during COVID. But the cost of providing supplemental instruction to tens of millions of students can be eye-watering, even as the results seem to taper off as programs serve more students.
That’s where artificial intelligence could prove a decisive advantage. A report circulated in October by the National Student Support Accelerator found that an AI-powered tutoring assistant significantly improved the performance of hundreds of tutors by prompting them with new ways to explain concepts to students. With the help of the tool, dubbed Tutor CoPilot, students assigned to the weakest tutors began posting academic results nearly equal to those assigned to the strongest. And the cost to run the program was just $20 per pupil.
Faculty must have the time and support necessary to come to terms with this new technology and that requires us to change how we view professional development in higher education and K-12. We cannot treat generative AI as a one-off problem that can be solved by a workshop, an invited talk, or a course policy discussion. Generative AI in education has to be viewed as a continuum. Faculty need a myriad of support options each semester:
Course buyouts
Fellowships
Learning communities
Reading groups
AI Institutes and workshops
Funding to explore the scholarship of teaching and learning around generative AI
Education leaders should focus on integrating AI literacy, civic education, and work-based learning to equip students for future challenges and opportunities.
Building social capital and personalized learning environments will be crucial for student success in a world increasingly influenced by AI and decentralized power structures.
Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.
We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.
Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.
Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.
Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1
Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.
Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.
…
Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.
Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…
… The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.
“We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
“If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.
The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.
Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.
Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.
The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.
The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.
Picture your enterprise as a living ecosystem,where surging market demand instantly informs staffing decisions, where a new vendor’s onboarding optimizes your emissions metrics, where rising customer engagement reveals product opportunities. Now imagine if your systems could see these connections too! This is the promise of AI agents — an intelligent network that thinks, learns, and works across your entire enterprise.
Today, organizations operate in artificial silos. Tomorrow, they could be fluid and responsive. The transformation has already begun. The question is: will your company lead it?
The journey to agent-enabled operations starts with clarity on business objectives. Leaders should begin by mapping their business’s critical processes. The most pressing opportunities often lie where cross-functional handoffs create friction or where high-value activities are slowed by system fragmentation. These pain points become the natural starting points for your agent deployment strategy.
Artificial intelligence has already proved that it can sound like a human, impersonate individuals and even produce recordings of someone speaking different languages. Now, a new feature from Microsoft will allow video meeting attendees to hear speakers “talk” in a different language with help from AI.
What Is Agentic AI? — from blogs.nvidia.com by Erik Pounds Agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems.
The next frontier of artificial intelligence is agentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. And it’s set to enhance productivity and operations across industries.
Agentic AI systems ingest vast amounts of data from multiple sources to independently analyze challenges, develop strategies and execute tasks like supply chain optimization, cybersecurity vulnerability analysis and helping doctors with time-consuming tasks.
