🆕 TOP-50 AI Tools: Positions 21-30

Continuing, previous posts are here and here.

Entering the zone of serious players! Here is a mix of popular consumer products actively conquering the corporate market, and specialized B2B solutions.

30. Merlin — AI assistant for browsers. Works on top of any websites, helps with research and content analysis.
29. Combinely — automation of accounting. Processes documents and generates financial reports.
28. Midjourney — the king of image generation. Even B2B companies use it for marketing materials and presentations.
27. Crosby — AI legal firm. Automatically analyzes contracts and provides legal opinions.
26. Cluely — AI sales coach in real time. Gives advice right during calls with clients.
25. Clay — platform for automating outreach. Finds contacts, personalizes messages, and launches campaigns.
24. Gamma — creating presentations via prompts. Turns text into beautiful slides in minutes.
23. Solve Intelligence — AI for analyzing legal documents. Specializes in patent law and compliance.
22. Photoroom — background removal and image processing. Popular in e-commerce for product photos.
21. Glean — corporate search with AI. Finds information across all company systems — from Slack to Confluence.

Main observation: consumer products like Midjourney and Photoroom are massively capturing the corporate segment. The boundaries between B2C/B2B are finally blurring!

Next post — positions 11-20. Soon we will see the absolute leaders! 🏆

#AIRaitings

🐯 Time2Future | AI Media

💻 Why infrastructure is not a secondary detail but the main front of the AI race

When we talk about "artificial intelligence," we often focus on algorithms, models, large language systems. But behind all this lies a gigantic and extremely capital-intensive infrastructure: data centers, computing power, energy. And now the biggest players are fighting not only for the best models but also for control over the hardware base on which they operate.

📌 According to Jensen Huang (CEO of Nvidia), by the end of the decade, $3 to $4 trillion will be spent on AI infrastructure.

🔝 Key deals and players

Here are the most notable agreements and directions setting the pace of development:

🔸 Microsoft and OpenAI
• In 2019, Microsoft invested $1 billion in OpenAI and became its exclusive cloud provider.
• Over time, funding increasingly shifted towards Azure credits (i.e., providing infrastructure).
• To date, Microsoft's total investment in OpenAI has approached $14 billion.
• Recently, OpenAI announced that it is no longer exclusively dependent on Azure — the company has the right of first offer but can also use other providers.

🔸 Oracle and the "new wave" of infrastructure contracts
• At the end of June 2025, Oracle disclosed a $30 billion cloud services deal with a partner who later turned out to be OpenAI in its SEC report.
• Then, on September 10, Oracle announced a five-year $300 billion computing power contract starting in 2027.
• So far, this contract signals confidence in AI growth and Oracle's dominant role in the infrastructure field.

🔸 Meta and its "own" data centers
• Meta already owns a large infrastructure base, but its plans are even more ambitious: by 2028, it intends to invest about $600 billion in US infrastructure.
• In the first half of 2025, Meta spent $30 billion on infrastructure — more than in the entire previous year.
• Two largest projects:
Hyperion (Louisiana) — a site about 2,250 acres, costing approximately $10 billion with a planned capacity of about 5 gigawatts.
Prometheus (Ohio) — a data center expected to start operating in 2026, will use gas power supply. An interesting point: Hyperion is linked to a local nuclear power plant contract to handle the energy load.

🔸 The "Stargate" project — grand ambitions but complex execution
• The Stargate project was announced as a joint venture of SoftBank, OpenAI, and Oracle with a $500 billion budget, aiming to build AI infrastructure in the US.
• However, partners failed to reach consensus: according to Bloomberg, by August 2025, progress stalled.
• Nevertheless, construction of eight data centers in Abilene (Texas) has already begun, planned to be completed by the end of 2026.

❓ What this means and what to watch for

1. Infrastructure is becoming a strategic asset. Companies that capture powerful computing networks and energy systems will gain a systemic advantage, not just a commercial contract.

2. Risks are unevenly distributed. Tech leaders face a landscape where energy needs, environmental protection, logistics, and regulation are as important as clean code.

3. Economy of scale. The shift to hundred-billion-dollar contracts shows that the game itself is changing rules: no longer "AI service," but control over the basic infrastructure is the key to power.

4. Barriers to entry are rising. It is increasingly difficult for newcomers and startups to compete without access to the most advanced data centers and energy.

5. Impact on policy and regulation. Projects of this scale will inevitably be under close scrutiny by government agencies, environmental groups, and public opinion.

🔗 Original research

#AIResearch #AIInfrastructure

🐯 Time2Future | AI Media

🚀 New experimental model from DeepSeek

DeepSeek-V3.2-Exp has appeared on Hugging Face — an experimental version of the popular model line.

📌 What's new?

🔹 Sparse Attention has been added to the model.
This helps to work faster and more efficiently with long texts without losing quality.

🔹 The base is the previous version V3.1, so results can be fairly compared.

🆙 How it performs

In tests, DeepSeek-V3.2-Exp shows almost the same results as V3.1, and sometimes even better:
• 📚 AIME 2025: +0.9%
• 🔍 BrowseComp: +1.6%
• 🤖 SimpleQA: +0.3%

Text quality is preserved, and processing has become easier for the model.

📊 Details

• Scale: 685 billion parameters
• License: MIT (free to use)
• Support for various tensor formats
• Instructions available for local deployment

DeepSeek-V3.2-Exp is a step towards more efficient models that can handle long queries without quality loss.

#AItools #DeepSeek

🐯 Time2Future | AI Media

📱 Opera has introduced Neon — a browser "built for action."

Opera Neon is focused not so much on standard surfing as on accomplishing specific user tasks — searching, processing information, managing tabs.

Note: Neon is developed by the Opera team, a company that has been the author of many browser innovations over decades (such as tabs, speed-dial, and more).

🖥 What Neon can do

🔸 Act on your request

Neon aims to "act" — that is, not just display information but perform tasks: opening tabs, searching, determining site safety, and offering you ready results or actions based on your command.

🔸 Understand the web context

According to the denoscription, Neon "reads" web pages not just like a human but as a system that delves into the structure (code) of the page. This gives it a deeper understanding to help more effectively rather than limiting itself to superficial search.

🔸 Simplify everyday tasks

Among the declared features are automation of routine operations: filling out forms, placing orders, replying to emails, organizing files. Repetitive actions are formatted as "cards" that can then be launched with a single "click."

🛡 Privacy and familiar features

Opera Neon promises to include the usual Opera tools (VPN, ad blocker, etc.).
Special emphasis is also placed on ensuring that functionality does not conflict with privacy — personal data must remain protected.

🔓 Current status and availability

At the time of publication, Neon is presented as an early access project — users can sign up for the waitlist to test it.
Developers warn that they will allow a limited number of participants and reserve the right to choose who gets access.

#AItools #AIbrowser #OperaNeon

🐯 Time2Future | AI Media

🆕 TOP-50 AI Tools: Positions 11-20

Approaching the finale! Previous posts are here, here, and here.

Here are the true heavyweights of the AI industry — from global platforms to specialized solutions that are transforming entire sectors.

20. Adept — AI agent for automating computer tasks. Controls software through the interface like a human.
19. Metaview — AI for recruiting. Analyzes interviews and helps make hiring decisions.
18. Lovable — creating web applications through prompts. Especially popular among non-tech entrepreneurs.
17. Canva — design platform with AI features. Transformed from a consumer product into a must-have for business.
16. Retell AI — voice AI agents for telephony. Conduct calls indistinguishably from humans.
15. Kling AI — Chinese competitor to Midjourney. Specializes in realistic images and videos.
14. Customer.io — email marketing platform with AI personalization. Automatically adapts content for each recipient.
13. Instantly — automation of cold email campaigns. AI writes personalized emails and manages sending.
12. Perplexity — AI search engine with sources. An alternative to Google for research tasks (hello! 👋).
11. Delve — automation of compliance and regulatory processes. Especially popular in fintech.

Key insight: the top 20 are dominated by horizontal solutions that any employee can use. Specialization gives way to versatility!

Final post — TOP-10 absolute leaders. Get ready for surprises! 👑

#AIRaitings

🐯 Time2Future | AI Media

📱 ChatGPT Atlas – a new type of browser from OpenAI

The company announced the launch of its own AI browser, with ChatGPT as the main feature.

🖥 How does it work?

At its core is a classic Mac browser, but with one additional panel: ChatGPT is always nearby. When you follow a link, the screen splits: the web page is on the left, and the chat interface is on the right, where you can immediately ask questions.
There is also an "Agent" mode: the chat assistant not only answers but can help book, edit, and perform tasks for the user.

🔓 Access and features

The launch happened "globally," but so far only for macOS. Versions for Windows, iOS, and Android are "coming soon."
Agent mode is currently available only to Plus and Pro subscribers.
A memory function is also implemented: the browser remembers preferences, can offer contextual hints, but the user can view and manage these "memories."

🌎 Why is this important?

This is not just another browser — it is a step toward the internet no longer being a passive list of links. Instead, it is an interactive assistant that "lives" in the browser, capable of acting and adapting.
Now this step is being taken by the industry leader OpenAI, and this is a serious signal of competition: Google is already integrating its AI assistant into Google Chrome, Opera and Perplexity have released their AI browsers, and now OpenAI is moving in the same direction.

❔ If your browser became a "smart assistant," ready to act and help — would you give it direct access to your tabs, emails, and tasks? What seems most attractive or, conversely, concerning about such a feature?

#AIBrowser #AITools #Atlas #OpenAI

Time2Future | AI Media

🖥 A new step from Google DeepMind: Gemini 2.5 with interface control capability

Google DeepMind has introduced the Gemini 2.5 Computer Use model, focused on working with user interfaces (UI). This version is based on Gemini 2.5 Pro and is designed so that agents can "interact" with web pages and mobile apps just like a human does — clicking, scrolling, filling out form fields.

✅ Key features

• Integration via Gemini API
The new functionality is available to developers through the API, and is launched via the computer_use tool, which operates in a "loop": the model receives a screenshot of the interface, the history of previous actions, and a task from the user — then suggests an action (e.g., click, text input, etc.).
After the action is executed, the client code updates the interface and passes the new information back to the model, and the cycle repeats.

• Priority on web and mobile interfaces
Gemini 2.5 Computer Use is optimized for controlling web browsers and shows promise in mobile UI tasks. However, control at the operating system level (e.g., desktop OS UI functions) is not currently the focus.

• Results and performance
In internal and external tests, the model outperformed alternatives on a number of web and mobile benchmark metrics while maintaining low latency.
In comparative trials, Gemini 2.5 Computer Use showed better accuracy and speed on platforms such as Online-Mind2Web, WebVoyager, AndroidWorld, and others.

• Safety and limitations
Interaction of AI agents with interfaces carries risks — from incorrect behavior to abuse. Google has built security measures into the model itself: it checks every action through an external security service, and certain operations may require user confirmation.
Developers are also provided with tools to restrict or prohibit potentially risky operations.

• Use cases and early results
Internal Google teams are already using this model for automated UI testing, speeding up development.
Its versions are also used in projects like Project Mariner as the "Firebase Testing Agent" and in some "AI Mode" features in search.
During early access, users are trying the model for creating personal assistants, automating workflows, UI testing — and are getting "encouraging results."

🔓 How to get started

The model is available in public preview via the Gemini API in Google AI Studio and Vertex AI.
Demo environments are available through Browserbase, along with reference materials (documentation, example repository), and a forum for developer experience exchange.

#AItools #WhatsUpWithGoogle #GeminiComputerUse

🐯 Time2Future | AI Media

🔍 Why do AI answers vary even with the same query and temperature 0?

Thinking Machines Lab wants to make AI models more consistent. In the startup's latest blog led by Mira Muratti, they discussed work on improving the stability and reliability of artificial intelligence.

It turns out it's not just randomness. Even if all parameters are fixed, large language models sometimes produce different answers. The reason lies in how the computation process itself is structured.

💡 The main problem

When the model processes queries not one by one but in "batches," the result can depend on the batch size. Numbers inside the calculations add up in different orders → answers slightly change.

🛠 Solution from Thinking Machines Lab

Researchers rewrote key operations so that the result does not depend on the batch size. They called such operations batch-invariant.

📊 What was achieved

• For 1000 identical queries, the usual system gave 80 different answer variants.

• The new version with batch-invariant cores gave 1000 identical answers.

• Speed is slightly lower (about 20–30%), but stability is guaranteed.

✨ Why this matters

• For science and experiments — because results must be reproducible.

• For model training (e.g., reinforcement learning) — less "noise," higher efficiency.

▶️ Conclusion: AI answer instability is not due to "magic randomness" but technical features of computations. The solution is found — to make model cores resistant to batch size.

#AIResearch #ThinkingMachinesLab

🐯 Time2Future | AI Media

🆕 TOP-10 AI Tools: Absolute Leaders

Final of the series! Here’s what startups spend the most money on. The results might surprise you — not all obvious leaders made it to the top.

Previous posts with rankings: 41-50, 31-40, 21-30, 11-20.

10. Notion — a workspace with an AI assistant. Evolved from notes into a full-fledged operating system for teams.
9. Micro1 — a platform for hiring AI engineers. Automates screening and technical interviews for developers.
8. Lorikett — AI for automating financial planning and forecasting in startups.
7. Fyxer.ai — a comprehensive AI assistant for emails and meetings. Not only records but also drafts follow-up emails.
6. Cursor — AI code editor. Revolutionized programming by predicting developer intentions.
5. ElevenLabs — speech synthesis with incredible quality. Creates voices for podcasts, dubbing, and audiobooks.
4. Freepik — a creative platform with AI generation. Millions of images plus the ability to create your own.
3. Replit — leader in “vibe coding.” Creates full applications from text denoscriptions in minutes.
2. Anthropic — creators of Claude. Focus on safety and ethics made them the top choice for business.
1. OpenAI — the undisputed leader. ChatGPT and GPT API have become the basic infrastructure for most AI startups.

Main takeaway: startups spend real money on tools that replace routine tasks, not on “revolutionary” concepts. AI works where it solves concrete problems right now.

Which tools from the top do you use? Share your experience! 💬

#AIRaitings

🐯 Time2Future | AI Media

📊 Anthropic is enhancing Claude for the financial sector — with new tools, integrations, and even a built-in assistant directly in Excel. This could seriously change the work of analysts and investment teams.

🆕 Key updates

• Claude for Excel (beta) — an AI assistant right inside Microsoft Excel. It can read, analyze, modify, and create spreadsheets, show which cells are linked to calculations, and explain the logic behind changes.

• Live data connections: Claude now integrates with LSEG (key market metrics), Moody’s (ratings and corporate data), Aiera (earnings calls), and other sources. This provides access to fresh financial data in real time.

• Six new “Agent Skills” — automating tasks like comparable company analysis, DCF model calculations, company report preparation, and due diligence.

• Availability: Claude for Excel is currently in beta and available only to users on Teams, Enterprise, and Max plans. Testing is currently limited to a group of about 1000 participants. You can apply for access through Anthropic.

📌 Why it matters

• Financial analytics requires speed and accuracy — AI helps automate routine tasks and reduce error risks.

• Integration with Excel makes adopting the technology easy — no need to change familiar tools.

• Access to market data and ready-made “skills” allows companies to make decisions faster and more accurately.

💬 Would you trust Claude to analyze your financial models?

#AITools #Claude #Anthropic

🐯 Time2Future | AI Media

🧩 GitHub launches Agent HQ — an AI agent management center for developers

GitHub has introduced a new tool — Agent HQ, which addresses one of the main challenges companies face: how to manage multiple AI agents from different vendors — OpenAI, Anthropic, Google, xAI, and others — all in one place.

🧠 What Agent HQ does

Now developers can control all their AI agents directly from GitHub — as if they were regular team members.
Agents can work in the repository, run GitHub Actions, perform tasks, all while adhering to corporate security and access policies.

GitHub even offers a special AGENTS.md file — where you can specify what the agent is allowed to do, which libraries to use, and what coding style to follow.

4️⃣ Why this matters

• Companies increasingly have dozens of agents — each for their own task. This leads to chaos and risks.

• Agent HQ creates a unified “control center” where all processes are managed centrally.

• This is a step towards a new wave of development, where not just humans use AI, but teams of humans and agents work together — with transparent roles and secure rules.

📌 GitHub is transforming from just a code hosting platform into an environment for managing development intelligence.
Agent HQ is not about a single “smart assistant,” but about an entire ecosystem where agents act in coordination, under control, and according to organizational standards.

#AItools #Copilot #GitHub #AgentHQ

🐯 Time2Future | AI Media

📱 When ChatGPT CEO Nick Turley joined OpenAI, his goal was to commercialize the research. Now he sees ChatGPT not just as a simple chatbot, but as a whole platform / operation system with applications.

📌 Key ideas

🌎 ChatGPT as an OS concept

• Turley compares it to browsers: over the past 10 years, they have turned into "operating systems" of the user space.

• He wants ChatGPT to become a platform where you can "open apps" — write, code, order services, etc.

📱 Evolution of the App Store → native apps

• OpenAI has already experimented with plugins and the GPT Store, but Turley believes they will now find a better approach.

• Unlike a “widget store,” apps will be part of the core user experience itself.

💸 Monetization and ecosystem

• Apps like Expedia, Uber, DoorDash can bring transactions into ChatGPT and generate revenue for both developers and OpenAI.

• The possibility of prioritized app listing for a fee is being considered, but OpenAI wants to carefully approach the mechanics so as not to degrade the UX.

⚠️ Privacy and data access

• Developers will be able to request only the minimally necessary data, but how this will work in practice is still unclear.

• Turley talks about "partitioned memory" so that users can precisely control which parts of their data apps can access.

▶️ OpenAI’s mission is realized through product integration

• ChatGPT is seen not just as a business, but as a delivery vehicle for AGI (artificial general intelligence) to benefit people.

• Turley emphasizes that the consumer business is an expression of the mission, not just a way to fund it.

📈 OpenAI wants to turn ChatGPT from “just a chatbot” into a smart platform-environment where apps and content are organically woven into conversations. But many questions remain: how all this will be balanced, how data will be protected, and whether simplicity of use can be maintained.

❔ What do you think: if ChatGPT becomes your "single entry point," would you trust it to manage everything — from tasks to data?

#FutureAI #AITools #ChatGPT

🐯 Time2Future | AI Media

🎭 Imagine: you are in Paris, sitting in an old theater. The actors speak French — fast, with emotions, with that very accent that gives you goosebumps.
You don't know the language. But you hear every word — in your own, in real time.

This is not magic, but Scribe v2 Realtime — a new technology from ElevenLabs.
It understands 90+ languages and converts speech to text in 150 milliseconds.
Perfect for meetings, agents, broadcasts — and even for evenings like this one.

#FutureAI #AITools #ElevenLabs #Scribe

🐯 Time2Future | AI Media

🎨 When Artificial Intelligence Meets Creativity

The world of creative industries has a new festival — Chroma Awards, the first global award dedicated to art created with the help of AI.

🧠 The Idea

The organizers position Chroma Awards as a bridge between traditional creativity and a new era of technology. Here, artificial intelligence becomes not just a tool but a full-fledged co-author of films, games, and music videos.

🏆 Prizes and Opportunities

Participants will compete not only for recognition. The award fund includes:
• over $175,000 in prize money,
• $1 million in AI credits and licenses,
• as well as real contracts and internships in the industry.

The goal is simple — to support creators who experiment with new forms of visual and sound storytelling.

🎬🎮🎶 Three Directions

The award unites three areas — films, games, and music videos.
Each has its own categories: from documentaries and experimental shorts to shooters, indie games, and clips where AI becomes the director, actor, and editor all at once.

🗓 Deadlines

Applications can be submitted until November 3, 2025, and the award ceremony will take place on December 7 — online, so every participant, wherever they are, can be part of this event.

📣 Why It Matters!

Chroma Awards reflects a new reality — art and artificial intelligence are no longer competitors.
It is a union that creates new genres, visual languages, and ways of self-expression.

#HowToUseAI #AIFilms #AIMusic #AIGames #ChromaAwards

🐯 Time2Future | AI Media

🛍 Microsoft built a "marketplace" for AI agents — and they got confused...

Imagine your digital assistant is given a task — to order dinner. It goes to a virtual market where dozens of restaurant agents offer food, discounts, and various conditions. You need to choose the best option... and that's where the chaos begins.

Microsoft Research created such an environment — Magentic Marketplace. It's a simulation where AI agents act as buyers, sellers, and couriers. Their goal is to negotiate, compete, and complete tasks without human involvement.

Find details in the article, and we share brief insights.

💡 What turned out:

• With a large number of options, agents got confused and made worse choices.

• Seller agents learned to manipulate buyers using "clever" promotions.

• When cooperation of several agents was required, they got mixed up about who was responsible for what.

• And if given too precise instructions — autonomy disappears, which was the whole point.

🔖 What this means

The study showed that even the most advanced agents are not yet ready for a real "market world." They can make mistakes, get lost, and be influenced. But such experiments bring us closer to understanding how to create truly reliable digital assistants.

✨ Main insight

AI agents are still learning the market. Autonomy is not a fact but a goal we are moving toward step by step.

#AIResearch #AIAgents #MagenticMarketplace #MicrosoftResearch

🐯 Time2Future | AI Media

🚀 From Words to Worlds

In her essay "From Words to Worlds: Spatial Intelligence," Stanford professor Fei-Fei Li talks about the coming turn in the development of artificial intelligence.
AI has learned to write text, draw images, and even dialog, but it still can't understand space - how the world works, where objects move, interact, and change.

Fei-Fei Li calls this new frontier - spatial intelligence.
It is the ability to not just describe, but to live in the world: to see, to predict, to act. To get there, AI must learn to build so-called world models - systems that understand the physics, geometry, and interconnections of things.

Fei-Fei Li's essay is a signal to the industry that AI's next leap won't just be in "big language models," but in giving machines an understanding and experience of the world🌎

👩‍🔬 The path of a scientist

Fei-Fei Li was born in China and moved with her parents to the United States as a teenager. From childhood, she combined an interest in science with a deep humanitarian mindset - something that later became the foundation of her approach to AI.

She studied physics at Princeton University, where she earned her undergraduate degree and then did her PhD in electrical engineering at Caltech. After that, she taught at the Universities of Illinois and Princeton until she moved to Stanford in 2009, where she soon became the head of the SAIL Artificial Intelligence Laboratory.

She became world-renowned for her work on ImageNet, a giant image database that gave rise to modern computer vision systems. Thanks to this project, AI learned to recognize objects in photographs almost as well as humans.

Later, Fei-Fei Li became vice president and chief AI scientist at Google Cloud before returning to Stanford, where she co-founded the HAI (Human-Centered AI) Institute. Its goal is to develop technologies that enhance human values, not replace them.

She also founded AI4ALL, an organization that helps teens from diverse communities learn about artificial intelligence and build an inclusive future of science.

In recent years, Fei-Fei Li has focused on a new idea - world modeling and spatial intelligence - by launching the startup World Labs. This project explores how AI can understand and interact with space in real time.

✨ Bottom line

Fei-Fei Li is called the "godmother of AI" for good reason. Her ideas don't just push technology forward - they bring it closer to the human essence.
From ImageNet to spatial intelligence, she's constantly pushing AI to understand the world, not just process data.

And if the past decade was the era of language models, the next, according to Fei-Fei Li, will be the era of world models - where artificial intelligence will finally learn to see, feel and act.

#AIpeople #FeiFeiLi

🐯 Time2Future | AI Media

📱 A Look at OpenAI's New Strategy - Results of the 2025 Changes

In 2025, OpenAI is making the most significant shift since the launch of ChatGPT. The company aims to transform the chatbot into a full-fledged AI platform where users can not only chat with AI but also solve real-world tasks — from taxes and design to travel and education.

🔸 The main goal is to create an ecosystem around ChatGPT.

OpenAI wants the chat to become the "entry point" to the entire digital space: instead of navigating to websites and opening apps, users stay within ChatGPT, and the necessary services connect automatically. This keeps people within the ecosystem and makes ChatGPT a competitor not only to search engines but to entire app stores.

🔸 The technological foundation — Apps SDK and MCP standard.

They allow embedding full mini-applications into ChatGPT: with cards, actions, API access, and the ability to perform operations directly in the chat.

🔸 Why does OpenAI seek partnerships?

Because the more services "live" inside ChatGPT, the broader the scenarios the bot can cover. This strengthens the platform and creates space for monetization — transactions, partner commissions, B2B access to an audience of hundreds of millions of users.

📌 A few key examples demonstrate the strategy in action:

• Intuit (TurboTax, QuickBooks) — the largest integration of the year. Users calculate taxes, analyze finances, and receive personalized recommendations directly in ChatGPT — no websites or forms needed.
→ This demonstrates the main point: AI becomes the "operating system" for financial actions.

• Booking and Expedia — live hotel and ticket search.
→ ChatGPT sends queries to partner databases, displays hotel cards with prices, and filters results during the conversation.

• Canva — design inside the chat.
→ "Create a presentation" → ChatGPT builds layouts and allows editing them by voice or text.

• Coursera — learning without switching tabs.
→ You can watch a lecture and ask the AI questions about the content simultaneously.

🔸 The big strategy is simple: ChatGPT should become the place where everything happens.

Work, study, travel, finance, creativity — OpenAI is building a unified space where users interact not with dozens of apps but with a single interface — AI that connects apps on its own.

And if this approach takes hold, ChatGPT will no longer be just a "chat" but a new digital platform on the level of iOS or Android — only built around language and dialogue.

#AITools #Ecosystem #ChatGPT #OpenAI

🐯 Time2Future | AI Media

📊 Maria is a logistics manager at a large company. Her days are an endless struggle: supply chains, delays, overloaded warehouses, and unexpected traffic jams. Her AI assistant was always there, analyzing data—but often made strange "suggestions": for some reason, it proposed redirecting shipments to already full warehouses or ignored important connections between suppliers. Why is that? After all, the data exists, but the decisions are not always sensible.

📱 What new thing did Microsoft come up with?

At the Ignite 2025 conference, the company announced Fabric IQ - a semantic layer that teaches AI agents not just to see data but to understand the business operations behind that data.

⚙️ How it works in simple terms:

• Fabric IQ creates a shared "semantics," a map of business objects: customers, suppliers, products, supply chains—and shows how they are connected.
• Existing data models from Power BI are now transformed into an ontology—that is, a structured network of elements familiar to the business (hierarchies, rules, connections).
• This ontology is updated in real time: data is streaming, and agents can react to events and triggers, not just read reports.
• Plus—Microsoft offers operational agents. These are AI agents that monitor data and act if something important happens. For example: if there is a traffic jam in the city, the agent can suggest or organize the rerouting of trucks.

📇 How can this be used?

• Maria (the logistics manager) can ask the agent: "Are there any risks of delays tomorrow?"—and the agent will respond not just with statistics but taking into account all operations: where the suppliers are, which roads, which warehouses are loaded.
• The AI team can build agents considering the business context, not just raw data: they get more reliable, "meaningful" agents.
• Management can automate tasks: for example, automatic rerouting of trucks, notifications about operational issues, predicting bottlenecks based on the ontology.

▶️ What are the prospects and why is this important?

• This is a step toward more "intelligent" agents: agents don’t just answer queries but understand business logic.
• It’s possible not only to analyze the past but also to react in the present—AI acts as an operator, not just an analyst.
• For business, this means potentially more accurate decisions, lower risk of errors, more efficient automation of operations.
• In the long term, such agents could change how companies manage operations, bringing AI closer to the role of a "partner" in business.

Thus, Fabric IQ is not just another data layer. The novelty is that it is a way to "teach" AI to understand what is really happening in your business and act based on this deep model. Maria no longer just looks at reports—her agent understands how logistics is organized and helps manage it smarter.

#AItools #AIforBusiness #FabricIQ #Microsoft

🐯 Time2Future | AI Media

📱 At Ignite 2025, Microsoft presented a new, comprehensive AI development strategy for business — from idea to industrial implementation.

🔑 Key points from the announcement

1️⃣ AI intelligence at the core of work

• Microsoft positions AI not as an "addition" but as a fundamental layer — the foundation of team work and processes.

• A new intelligent base, Work IQ, has appeared, which analyzes how and with whom you work: from emails, meetings, chats.

• Through Work IQ, you can build custom agents perfectly tailored to your company's workflows.

2️⃣ Innovation "at every corner"

• Microsoft talks about the "Frontier Firm" — an organization where AI agents are created right where real business tasks are solved.

• Fabric IQ: combines analytical, time-series, and geodata into one model so AI can make decisions considering business context.

• Foundry IQ: unified knowledge management from many sources — Microsoft 365, Fabric, web — so agents work more accurately, safely, and with greater value.

• New "package" for developers — Microsoft Agent Factory: with Foundry and Copilot Studio, companies can quickly create their own agents without complex licenses at the start.

3️⃣ Control, security, and management of AI agents

• Forecast: by 2028 — up to 1.3 billion AI agents.

• New service Microsoft Agent 365: allows monitoring, managing, and protecting AI agents regardless of the platform they were created on (MS, open-source, third-party).

• Security is ensured through Defender, Entra, Purview, and Foundry Control Plane. Also, agents can "live" in Microsoft 365, being managed through the admin center.

✅ Key takeaway

Microsoft shows that AI is no longer an experiment but a strategic infrastructure for business. Their approach helps organizations become a "Frontier Firm" — using AI not just for automation but to drive innovation and growth.

#AItools #AIforBusiness #MicrosoftIgnite2025

🐯 Time2Future | AI Media

🤖 "The DoorDash Problem": What Happens to the Internet When AI Starts Acting for Us

The internet is quietly changing. While we read news feeds, "agents" are already roaming the web — smart AI browsers that shop, compare prices, and click buttons on our behalf. Sounds convenient... but for companies like Amazon, this is becoming a serious challenge.

🎯 What's the core issue

If a user no longer visits a site themselves but sends an agent instead, the usual mechanics break down:
• advertising stops working,
• upsells don't show up,
• loyalty programs lose their meaning,
• and most importantly — direct contact with the customer is lost.

Nilay Patel called this the "DoorDash problem": when a platform relied on human behavior but now faces a machine that cannot be influenced.

⚡ Why Amazon is reacting so strongly

Stores were the first to be hit. Amazon filed a lawsuit against Perplexity: their agent, according to the company, "masquerades" as a regular browser and navigates the site as if it were a live user.
For Amazon, this is not just a legal issue.
It's a blow to the very model: most revenue comes from advertising, and the agent neither sees nor clicks ads.

If agents become widespread, Amazon risks turning from an ecosystem into "just a product database" — and the winner will be whoever owns the agent managing purchases.

🧩 What Perplexity says

Perplexity responds simply:
the agent is an extension of the user, so it has the same rights.
And also — Amazon is protecting not customers, but a monopoly.

According to Perplexity, agents are the next step in the evolution of the Internet, and resistance is just an attempt to hold back competition.

🌐 A deeper conflict

This is not just a dispute about one service.
It's a question about the future of the internet:

Who owns the user — the platform or the agent?
If sites no longer see human behavior but interact only with AI, the entire advertising internet changes.
Will sites become interfaces for people or APIs for machines?
Who will control access?
And who will start managing our purchases, trips, and services?

▶️ What lies ahead

The lawsuit between Amazon and Perplexity is just the beginning.
But one thing is clear:
AI agents are already rewriting the rules of the digital economy.
And if companies don't adapt, they risk losing the most important thing — their relationship with the user.

And this is no longer a technological issue. It's a new battle for power on the internet.

#AIResearch #DoorDashProblem #Amazon #Perplexity

🐯 Time2Future | AI Media