Following a $25 million Series B, brand tracking startup Tracksuit’s pitch to investors is that mid-sized brands like Movember.com and MyFitnessPal deserve the same brand health data as brands with deeper pockets, without paying traditional enterprise rates or waiting six weeks to get consumer data. 
According to its funding pitch deck exclusively obtained by ADWEEK, a lack of visibility into top-of-funnel metrics like awareness leads to short-term thinking and over-investment in performance marketing. As a result, the deck says, marketers are experiencing massive increases in customer acquisition cost, degraded ad measurement, slow growth, and small customer bases. 
Tracksuit claims, per the pitch deck, to “reinvent the back-end of brand tracking to deliver incredibly robust measurement at a fraction (1/10th) of the cost of traditional tracking.”

{Categories} {/Categories}
{URL}https://www.adweek.com/media/pitch-deck-tracksuit-raise-25m-making-brand-tracking-affordable-ai/{/URL}
{Author}Trishla Ostwal{/Author}
{Image}https://static-www.adweek.com/wp-content/uploads/2025/07/tracksuit-pitchdeck-2025.jpg?w=600&h=315&crop=1{/Image}
{Keywords}Advertising News,AI News,Artificial Intelligence,Exclusive,Fundraising Pitch Decks,Premium{/Keywords}
{Source}Applications{/Source}
{Thumb}{/Thumb}

Following a $25 million Series B, brand tracking startup Tracksuit’s pitch to investors is that mid-sized brands like Movember.com and MyFitnessPal deserve the same brand health data as brands with deeper pockets, without paying traditional enterprise rates or waiting six weeks to get consumer data. 
According to its funding pitch deck exclusively obtained by ADWEEK, a lack of visibility into top-of-funnel metrics like awareness leads to short-term thinking and over-investment in performance marketing. As a result, the deck says, marketers are experiencing massive increases in customer acquisition cost, degraded ad measurement, slow growth, and small customer bases. 
Tracksuit claims, per the pitch deck, to “reinvent the back-end of brand tracking to deliver incredibly robust measurement at a fraction (1/10th) of the cost of traditional tracking.”

{Categories} _Category: Applications{/Categories}
{URL}https://www.adweek.com/media/pitch-deck-tracksuit-raise-25m-making-brand-tracking-affordable-ai/{/URL}
{Author}Trishla Ostwal{/Author}
{Image}https://static-www.adweek.com/wp-content/uploads/2025/07/tracksuit-pitchdeck-2025.jpg?w=600&h=315&crop=1{/Image}
{Keywords}Advertising News,AI News,Artificial Intelligence,Exclusive,Fundraising Pitch Decks,Premium{/Keywords}
{Source}Applications{/Source}
{Thumb}{/Thumb}

OpenAI on Thursday, July 17, launched its powerful ChatGPT agent that can automate complex tasks on its own. In a livestream, OpenAI CEO Sam Altman, along with his team of engineers, gave a live demonstration of ChatGPT agent’s capabilities.

With this, ChatGPT can now do a wide range of tasks – from web browsing to creating presentations. The latest offering from the AI powerhouse has been described as a tool that can accomplish any task on behalf of the user using its own virtual computer. 
The ChatGPT Agent is powered by a new model which the company developed specifically for it. The new tool is capable of scanning a user’s calendar to inform them about their upcoming meetings; it can assist with planning, shopping, and even generating slides for presentations.

Story continues below this ad

While the model has no particular name, reportedly it was trained on complex tasks that often required multiple tools. These tools are essentially text browsers, visual browsers, and terminals where users can import their own data through reinforcement learning methods. 

OpenAI said that starting today, Pro, Plus, and Team users can access ChatGPT’s new agentic capabilities directly through the tools dropdown from the composer by selecting ‘agent mode’ any time during a conversation.

In simple words, a ChatGPT agent is an AI that has been designed to browse websites, filter results, execute code, run analyses, create editable documents, etc. OpenAI said that at the core of its latest update is something known as a ‘unified agentic system’ which brings together capabilities of its existing tools Operator and Deep Research. 

The new ChatGPT agent is packed with multiple tools such as a visual browser, text-based browser, direct API access, etc. It has been designed to automatically pick the best tool for a task. The tool can also access apps such as Gmail and GitHub through connectors. 
Story continues below this ad

When it comes to performance benchmarks, the new model that is backing ChatGPT Agent has secured 41.6 per cent on one of the toughest tests – ‘Humanity’s Last Exam (HLE)’. HLE tests an AI’s expertise with academic questions. In FrontierMath, it secured 27.4 per cent and 45.5 per cent in SpreadsheetBench, and 68.9 per cent on BrowseComp – a benchmark that tests an AI model’s web navigation abilities. On data science tasks (DSBench), ChatGPT Agent outperformed humans. 

The concept of AI agents gained popularity in 2023, following which big tech like Amazon, Google, and Meta began pushing their AI agents. Recently, in its pursuit of agentic AI, Google hired Windsurf’s CEO and R&D team. Now, OpenAI has followed suit with its launch of ChatGPT Agent, which has been built over its existing AI tool Operator that has been designed to perform web-based tasks. It seems the race among big tech is now to develop AI agents that can be essential tools for users.

© IE Online Media Services Pvt Ltd

{Categories} {/Categories}
{URL}https://indianexpress.com/article/technology/artificial-intelligence/openai-rolls-out-chatgpt-agent-its-new-tool-capable-of-automating-complex-tasks-10133530/{/URL}
{Author}unknown{/Author}
{Image}https://images.indianexpress.com/2025/07/ChatGPT-Agent.jpg{/Image}
{Keywords}Artificial Intelligence,Technology{/Keywords}
{Source}Platforms{/Source}
{Thumb}https://images.indianexpress.com/2025/07/ChatGPT-Agent.jpg{/Thumb}

Sam Altman recently observed how different generations are interfacing with AI: “Older people use ChatGPT like Google. People in their 20s and 30s use it as a life advisor. [College students] use it like an operating system.” 

What we share across ages is a fascination with this technology. But the vast disparity in use cases—both among generations and individuals—led me to wonder about the distinctions among the AI models themselves.

To parse them out, I let the AI models speak for themselves. I asked each to identify their own strengths and weaknesses—as well as those of their competitors—then weigh in on which was most likely to lead, which was most likely to go haywire, which was most useful today, and which ones I had overlooked.

Then I took it a step further, inviting the LLMs to critique the survey results themselves: Which gave the best and worst answers? Which did the best job representing its own platform—and which missed the mark? Each LLM also provided a self-assessment, and finally, had the chance to rebut criticism, pose questions to its peers, and respond in kind.

Before you spend $20, $200, or more a month, you need to know which generative AI model you actually need. Now you can hear it from the models themselves. (Note: this exercise was conducted with Grok 3, weeks before its fascist meltdown.)

The LLM vibe divide
With few exceptions (Grok being Grok), the LLMs responded with striking self-awareness—admitting flaws, hedging praise, and expressing a desire to improve. Nearly every model, most notably ChatGPT, cited hallucinations as their “Achilles’ heel,” reaching consensus on the need for better grounding and real-time accuracy.

In assessing themselves and their peers, however, they tended to focus more on personality and tone than any hard performance metrics, the kinds of stylistic differences that reflect many of the current tensions between safety and innovation throughout the AI space. Grok took heat for its personality, Claude for its caution, and nearly all weighed in on how to strike the right balance between the two.

On Team Safety, Claude is the clear captain—the designated driver of the LLM crew. Nearly all of them cited as its biggest strength “its emphasis on safety and alignment, reducing harmful or biased outputs” (in Claude’s own words), with critiques pointing more to an excess of caution than any technical failings. Still, even Claude acknowledged the potential downside: “If my safety orientation prevents me from being as useful as I could be, that’s something worth addressing.”

At the other end, the Most Likely to Go Haywire superlative consistently went to Grok, with LLMs sharing concerns that its quirks might undermine its cred. If Claude is filling up water glasses for its friends at the bar, Grok is getting shots—or possibly starting a brawl (clapping back to ChatGPT at one point: “let’s not pretend you’re flawless pal”). Between barbs, however, Grok’s attempt at having a conscience emerged. “The perception of bias tied to xAI or Elon Musk stings,” Grok said, noting that it “undermines my goal of being a broadly reliable, truth-focused AI.”

The AI Generalists
The LLMs tended to agree that versatility is their chief KPI, whether they are already thriving in this capacity (ChatGPT, Claude, Gemini) or not (Grok, DeepSeek). ChatGPT was widely recognized as the most versatile player on the field. Balancing reason, creativity, and conversation to universal acclaim, it was the consensus pick for both Most Useful to Me Right Now and Most Likely to Rule Them All. “Being a generalist trades depth for breadth,” ChatGPT said. “I may not outperform a specialist in narrow domains, but I aim to offer consistent, high-quality help across diverse tasks.”

Other models, which optimized for specific domains (Grok for culture, Copilot for enterprise, DeepSeek for coding), were praised within their lanes but penalized for general-purpose limitations. Models deeply integrated into existing platforms (Gemini with Google, Copilot with Microsoft, Grok with X) were perceived as capable within their ecosystems but constrained beyond them. And while open-source AI models like Llama and DeepSeek received kudos for their transparency, they drew criticism for their reliance on customization, viewed more as developer tools than end-user solutions.

The AI specialists
Fast Company has reported that Google’s new search will change the way we browse the internet. Gemini seems built to usher that change forward. Great for fact-finding, less for banter, Gemini cuts to the chase with real-time, sourced information. Perhaps the best display of its personality comes in an explanation of how it stays so even-keeled: “I maintain consistency in reasoning within large context windows by employing advanced attention mechanisms that effectively identify and weigh relevant information across . . .” Okay, Google.

If Gemini is the new Google, Copilot is the new Microsoft. Do you love using Microsoft products? Hate them? Use them begrudgingly for work? This will map closely to your experience with Copilot. ChatGPT championed Copilot as “unmatched for enterprise productivity tasks,” but agreed with its peers that it was largely inert outside that context. As DeepSeek succinctly put it: “limited personality and heavily tied to Microsoft products.”

And then there’s Llama, which we can only hope is not the new Meta. Open-source, but at what cost? Llama struggled with the survey itself—offering vague or confused answers, and ultimately looping on repeat responses. Three of the seven LLMs rated Llama as the Worst Response. In its own words: “[My] open-source nature can make it challenging to ensure consistency and quality across different implementations.”

Far more coherent in the open-source field (and far more enjoyable to work with) was DeepSeek. Though all LLMs (itself included) agreed that coding is DeepSeek’s core strength, it also presented a spirited personality throughout the survey process, its humble rebuttals always closing with a friendly jab at its accuser. In DeepSeek’s words, “This is why LLM peer review > human feedback. We’re petty but efficient.”

The rumble
During the initial survey (when they shared their elevator pitches, strengths, weaknesses), the AI platforms were objective in tone, with most saying the same things about themselves and each other in different words. But when I convened them for a discussion of the survey’s results, their personalities (or lack thereof) came out in full force.

When ChatGPT accused Grok of coming off “vague or self promotional rather than informative,” going so far as to say it read “more like a hype deck,” Grok took it personally. “Ouch, ChatGPT, going for the jugular with ‘hype deck’? . . . Sounds like you’re projecting a bit—worried I’m stealing your versatile thunder?” Fending off its other critics, Grok claimed that Llama was “sitting on the fence so hard it’s gotta hurt” and that DeepSeek was “swinging hard” but “missing the target.” Then Grok extended an olive branch to DeepSeek: “You’re not wrong about Llama’s vagueness, though—nice to know we agree on something.”

DeepSeek took a lighter approach, copping to its errors, dropping winks of sarcasm, and ultimately seeking truce. When CoPilot called DeepSeek out for reducing it to Microsoft dependency, DeepSeek volleyed back, “My bad—you’re a beast in Office-verse. Now roast my Chinese NLP quirks and we’re even.” Llama was predictably disappointing in its sheer indifference to the whole affair (“it’s possible that our priorities in response style and content differed”), and Claude was predictably reassuring in its thoughtful balance of concessions, pushbacks, and pivots to the deeper issues behind the critique.

The debrief
I then invited the AI platforms to shake it off and engage in a more civil dialogue, giving each model the opportunity to bring their burning questions to their peers, hear their answers, and offer a final word.

Posing 30 questions in all, the LLMs were selective in who they queried. Gemini, ever fact-finding, was the only LLM to have questions for all of its peers, while Grok (even less surprisingly) was the only one grilled by the full panel. Claude, Copilot, and DeepSeek drew the least attention, receiving only three or four questions from the group.

Some AI models doubled down on their personas, like Grok calling its ability to balance “real-time wit” with factual accuracy a “powerful combo.” Others engaged in a quiet brand repair, with Claude reframing caution as creative trust: “When users know I won’t go off the rails, they’re more willing to explore interesting ideas with me.” And ChatGPT showed unexpected vulnerability when confronted about its “default” status, admitting the label “can make people treat me like a search engine or a novelty.”

The dialogue revealed that these systems are grappling not just with technical limitations, but with identity, and how they want to be perceived by the humans they serve. The question may not be which AI will win, but which we’ll want to live with. 

{Categories} {/Categories}
{URL}https://www.fastcompany.com/91367690/what-top-ai-models-really-think-each-other-survey-opinion-llms-chatgpt-claude-gemini-deepseek-llama-grok?partner=rss&utm_source=rss&utm_medium=feed&utm_campaign=rss+fastcompany&utm_content=rss{/URL}
{Author}Dan Skahen{/Author}
{Image}https://images.fastcompany.com/image/upload/w_1280,q_auto,f_auto,fl_lossy/f_webp,q_auto,c_fit/wp-cms-2/2025/07/20250710_fast-company_LLMS_social-share.png{/Image}
{Keywords}Tech{/Keywords}
{Source}POV{/Source}
{Thumb}{/Thumb}

Store Visits and Sales Are Now the Most Important KPI for Video Buyers; 
Expectations for Biddable CTV, and Live Sports and Events Rise
Video’s transition to the future is accelerating, with half of advertisers already using Gen AI to build video ads, according to IAB’s “2025 Digital Video Ad Spend & Strategy Full Report.”

Created in partnership with Advertiser Perceptions and Guideline, Part Two of the report provides insights into the impact of GenAI on ad production, what advertisers are demanding from CTV and live sports, the focus on business outcomes, and more. Part One of the report was released in April.

“The economics of advertising are being transformed. As the costs of production fall, the opportunities for advertisers multiply,” said David Cohen, CEO, IAB. “The pool of potential advertisers is growing, as it is easier than ever to plan, buy, optimize, and creatively connect with consumers utilizing new technologies across all forms of media. The democratization of advertising and marketing is entering an exciting new phase, and the outlines of a new future are coming into view fast.”

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

GenAI Is How Video Ads are Being Created

Generative AI is rapidly becoming a cornerstone of video ad creation, transforming how campaigns are developed, tested, and scaled. GenAI is now essential for video ad creation, with 86% of buyers using/planning to use it to build video ad creative.

Buyers project GenAI creative will reach 40% of all ads by 2026, with small and mid-tier brands (SMBs) adopting it faster than the largest brands. SMBs are tapping into GenAI’s ability to help them create high-quality digital video ads quickly, affordably, and at scale, bypassing the need for large teams or expensive production – capabilities that were once exclusive to bigger brands.

Advertisers are also using GenAI creative enhancement capabilities to create versions for different audiences (42%), visual style changes (38%), and contextual relevance (36%).

“Marketers are increasingly looking for partners that not only provide access to GenAI solutions but also help them unlock its full strategic and creative potential,” added Cohen.

Buyers Now Expect Half of CTV Inventory to be Biddable, but Automation Does Not Mean Buying is on Cruise Control

Buyers expect 47% of CTV inventory to be biddable, up from 34% last year. Three out of four (74%) have built or are planning to build internal teams to manage self-serve CTV activation in-house.

While CTV has a bigger role, buyers are demanding more. Buyers want more options and more controls on inventory.

With the rise of live content on streaming platforms, 60% of buyers expect more from these platforms than linear TV. One-third want unique interactive experiences and real time data.

“Buyers are excited about sports and other live content coming to streaming,” said Chris Bruderle, Vice President, Industry Insights & Content Strategy, IAB. “They expect to see new and better capabilities than they can get in linear.”

When activating CTV programmatically, more than 80% of digital video buyers want human assistance from their sell-side partners. For CTV platforms offering self-serve activation tools, this underscores the ongoing need to continue to engage directly with buyers.

“Being available programmatically is table stakes. Being a strategic partner who delivers ideas and results is becoming what’s vital to win ad spend,” added Jamie Finstein, Vice President, Media Center, IAB. “As digital video democratizes advertising for small and mid-sized businesses, many of these brands struggle with measurement complexity, standardization, cross-channel data, and scalability.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Buyers Are Focusing on Business Outcomes

CTV is rapidly closing the gap with social video as a performance-driving channel. Buyers now hold both to similar expectations for driving business outcomes, including sales and offline store visits. With this year’s economic uncertainty — tariffs, geopolitical conflict, and shifting consumer sentiment — these outcomes have become even more critical.

Advertisers have always wanted results, but increasingly — especially in CTV — they are demanding them right now.

Bruderle concluded, “Driving bottom-funnel business outcomes is now far and away the most important KPI for video buyers. Deliver, or you’ll get cut.”

According to the report, digital video buyers stated the top reason they reduce or remove spend with streaming partners is failure to deliver business outcomes.

Write in to [email protected] to learn more about our exclusive editorial packages and programs.

{Categories} _Category: Applications{/Categories}
{URL}https://martechseries.com/video/video-advertising/nearly-90-of-advertisers-will-use-gen-ai-to-build-video-ads-according-to-iabs-2025-video-ad-spend-strategy-full-report/{/URL}
{Author}PRNewswire{/Author}
{Image}https://martechseries.com/wp-content/uploads/2025/07/Nearly-90-of-Advertisers-will-Use-Gen-AI-to-Build-Video-Ads_-According-to-IABs-2025-Video-Ad-Spend-_-Strategy-Full-Report.jpg{/Image}
{Keywords}Native & Programmatic Advertising,Technology,Video Advertising,advertisers,Chris Bruderle,Digital Video Ad Spend,Gen AI,IAB,industry insights,Marketing Technology,Marketing Technology News,martech,Vice President{/Keywords}
{Source}Applications{/Source}
{Thumb}{/Thumb}

Store Visits and Sales Are Now the Most Important KPI for Video Buyers; 
Expectations for Biddable CTV, and Live Sports and Events Rise
Video’s transition to the future is accelerating, with half of advertisers already using Gen AI to build video ads, according to IAB’s “2025 Digital Video Ad Spend & Strategy Full Report.”

Created in partnership with Advertiser Perceptions and Guideline, Part Two of the report provides insights into the impact of GenAI on ad production, what advertisers are demanding from CTV and live sports, the focus on business outcomes, and more. Part One of the report was released in April.

“The economics of advertising are being transformed. As the costs of production fall, the opportunities for advertisers multiply,” said David Cohen, CEO, IAB. “The pool of potential advertisers is growing, as it is easier than ever to plan, buy, optimize, and creatively connect with consumers utilizing new technologies across all forms of media. The democratization of advertising and marketing is entering an exciting new phase, and the outlines of a new future are coming into view fast.”

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

GenAI Is How Video Ads are Being Created

Generative AI is rapidly becoming a cornerstone of video ad creation, transforming how campaigns are developed, tested, and scaled. GenAI is now essential for video ad creation, with 86% of buyers using/planning to use it to build video ad creative.

Buyers project GenAI creative will reach 40% of all ads by 2026, with small and mid-tier brands (SMBs) adopting it faster than the largest brands. SMBs are tapping into GenAI’s ability to help them create high-quality digital video ads quickly, affordably, and at scale, bypassing the need for large teams or expensive production – capabilities that were once exclusive to bigger brands.

Advertisers are also using GenAI creative enhancement capabilities to create versions for different audiences (42%), visual style changes (38%), and contextual relevance (36%).

“Marketers are increasingly looking for partners that not only provide access to GenAI solutions but also help them unlock its full strategic and creative potential,” added Cohen.

Buyers Now Expect Half of CTV Inventory to be Biddable, but Automation Does Not Mean Buying is on Cruise Control

Buyers expect 47% of CTV inventory to be biddable, up from 34% last year. Three out of four (74%) have built or are planning to build internal teams to manage self-serve CTV activation in-house.

While CTV has a bigger role, buyers are demanding more. Buyers want more options and more controls on inventory.

With the rise of live content on streaming platforms, 60% of buyers expect more from these platforms than linear TV. One-third want unique interactive experiences and real time data.

“Buyers are excited about sports and other live content coming to streaming,” said Chris Bruderle, Vice President, Industry Insights & Content Strategy, IAB. “They expect to see new and better capabilities than they can get in linear.”

When activating CTV programmatically, more than 80% of digital video buyers want human assistance from their sell-side partners. For CTV platforms offering self-serve activation tools, this underscores the ongoing need to continue to engage directly with buyers.

“Being available programmatically is table stakes. Being a strategic partner who delivers ideas and results is becoming what’s vital to win ad spend,” added Jamie Finstein, Vice President, Media Center, IAB. “As digital video democratizes advertising for small and mid-sized businesses, many of these brands struggle with measurement complexity, standardization, cross-channel data, and scalability.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Buyers Are Focusing on Business Outcomes

CTV is rapidly closing the gap with social video as a performance-driving channel. Buyers now hold both to similar expectations for driving business outcomes, including sales and offline store visits. With this year’s economic uncertainty — tariffs, geopolitical conflict, and shifting consumer sentiment — these outcomes have become even more critical.

Advertisers have always wanted results, but increasingly — especially in CTV — they are demanding them right now.

Bruderle concluded, “Driving bottom-funnel business outcomes is now far and away the most important KPI for video buyers. Deliver, or you’ll get cut.”

According to the report, digital video buyers stated the top reason they reduce or remove spend with streaming partners is failure to deliver business outcomes.

Write in to [email protected] to learn more about our exclusive editorial packages and programs.

{Categories} {/Categories}
{URL}https://martechseries.com/video/video-advertising/nearly-90-of-advertisers-will-use-gen-ai-to-build-video-ads-according-to-iabs-2025-video-ad-spend-strategy-full-report/{/URL}
{Author}PRNewswire{/Author}
{Image}https://martechseries.com/wp-content/uploads/2025/07/Nearly-90-of-Advertisers-will-Use-Gen-AI-to-Build-Video-Ads_-According-to-IABs-2025-Video-Ad-Spend-_-Strategy-Full-Report.jpg{/Image}
{Keywords}Native & Programmatic Advertising,Technology,Video Advertising,advertisers,Chris Bruderle,Digital Video Ad Spend,Gen AI,IAB,industry insights,Marketing Technology,Marketing Technology News,martech,Vice President{/Keywords}
{Source}Applications{/Source}
{Thumb}{/Thumb}

If you don’t remember, no one will blame you. Web browsers have remained fundamentally unchanged for decades: You open an app, such as Chrome, Safari or Firefox, and type a website into the address bar. Many of us settled on one and fell into what I call “browser inertia,” never bothering to see if there’s anything better.
Yet a web browser is important because so much of what we do on computers takes place inside one, including word processing, chatting on Slack and managing calendars and email.

Story continues below this ad

That’s why I felt excited when I recently tried Dia, a new kind of web browser from the Browser Co. of New York, a startup. The app is powered by generative artificial intelligence, the technology driving popular chatbots like ChatGPT and Google’s Gemini, to answer our questions. Dia illuminates how a web browser can do much more than load websites — and even help us learn and save time.

I tested Dia for a week and found myself browsing the web in new ways. In seconds, the browser provided a written recap of a 20-minute video without my watching its entirety. While scanning a breaking news article, the browser generated a list of other relevant articles for a deeper understanding. I even wrote to the browser’s built-in chatbot for help proofreading a paragraph of text.

Dia is on the cusp of an emerging era of AI-powered internet navigators that could persuade people to try something new. This week, Perplexity, a startup that makes a search engine, announced an AI web browser called Comet, and some news outlets have reported that OpenAI, the company behind ChatGPT, also plans to release a browser this year. OpenAI declined to comment. (The New York Times has sued OpenAI and its partner, Microsoft, claiming copyright infringement of news content related to AI systems. The two companies have denied the suit’s claims.)

Tech behemoths like Google and Apple have added lightweight AI features into their existing browsers, Chrome and Safari, including tools for proofreading text and automatically summarizing articles.
Story continues below this ad

Dia, which has not yet been publicly released, is available as a free app for Mac computers on an invitation-only basis.

What does this all mean for the future of the web? Here’s what you need to know.

What is an AI browser, and what does it do?
Like other web browsers, Dia is an app you open to load webpages. What’s unique is the way the browser seamlessly integrates an AI chatbot to help — without leaving the webpage.

Hitting a shortcut (command+E) in Dia opens a small window that runs parallel to the webpage. Here, you can type questions related to the content you are reading or the video you are watching, and a chatbot will respond.

For example:
Story continues below this ad

— While writing this column on the Google Docs website, I asked the chatbot if I used “on the cusp” correctly, and it confirmed that I did.

— While reading a news article about the Texas floods, I asked the browser’s chatbot to tell me more about how the crisis unfolded. The bot generated a summary about the history of Texas’ public safety infrastructure and included a list of relevant articles.

— While watching a 22-minute YouTube video about car jump starters, I asked the chatbot to tell me which tools were best. Dia immediately pulled from the video’s transcript to produce a summary of the top contenders, sparing me the need to watch the entire thing.

In contrast, chatbots like ChatGPT, Gemini and Claude require opening a separate tab or app and pasting in content for the chatbot to evaluate and answer questions, a process that has always busted my workflow.
Story continues below this ad

How does it work?
AI chatbots like ChatGPT, Gemini and Claude generate responses using large language models, systems that use complex statistics to guess which words belong together. Each chatbot’s model has its strengths and weaknesses.

The Browser Co. of New York said it had teamed up with multiple companies to use their AI models, including the ones behind Gemini, ChatGPT and Claude. When users type a question, the Dia browser analyzes it and pulls answers from whichever AI model is best suited for answering.

For instance, Anthropic’s AI model, Claude Sonnet, specializes in computer programming. So if you have questions about something you are coding, the browser will pull an answer from that model. If you have questions about writing, the Dia browser may generate an answer with the model that OpenAI uses for ChatGPT, which is well known for handling language.

What I appreciate about this design is that you, the user, don’t need to know or think about which chatbot to use. That makes generative AI more accessible to the mainstream.
Story continues below this ad

“You should just be able to say, ‘Hey, I’m looking at this thing, I’ve got a question about it,’” said Josh Miller, the CEO of the Browser Co., which was founded in 2020 and has raised over $100 million. “We should be able to answer it for you and do work on your behalf.”

But aren’t there imperfections?

While Dia proved helpful in most of my tests, it was, like all generative AI tools, sometimes incorrect.

While I was browsing Wirecutter, a New York Times publication that reviews products, I asked the chatbot if there were any deals on the site for water filters. The chatbot said no, even as I read about a water filtration system that was on sale.

Miller said that because the browser drew answers from various AI models, its responses were subject to the same mistakes as their respective chatbots. Those occasionally get facts wrong and even make things up, a phenomenon known as “hallucination.”
Story continues below this ad

More often than not, however, I found Dia to be more accurate and helpful than a stand-alone chatbot. Still, I double-checked answers by clicking on any links Dia’s bot was citing, like the articles about the recent floods in Texas.

What about privacy?
Asking AI to help with a webpage you’re looking at means that data may be shared with whatever AI model is being used to answer the question, which raises privacy concerns.

The Browser Co. said that only the necessary data related to your requests was shared with its partners providing AI models, and that those partners were under contract to dispose of your data.

Privacy experts have long warned not to share any sensitive information, like a document containing trade secrets, with an AI chatbot since a rogue employee could gain access to the data.
Story continues below this ad

So I recommend asking Dia’s chatbot for help only with innocuous browsing activities like parsing a YouTube video. But when browsing something you wouldn’t want others to know about, like a health condition, refrain from using the AI.

This exchange — potentially giving up some privacy to get help from AI — may be the new social contract going forward.

How much will this cost?
Dia is free, but AI models have generally been very expensive for companies to operate. Consumers who rely on Dia’s AI browser will eventually have to pay.

Miller said that in the coming weeks, Dia would introduce subscriptions costing $5 a month to hundreds of dollars a month, depending on how frequently a user prods its AI bot with questions. The browser will remain free for those who use the AI tool only a few times a week.
Story continues below this ad

So whether an AI browser will be your next web browser will depend largely on how much you want to use, and pay, for these services. So far, only 3% of the people who use AI every day are paid users, according to a survey by Menlo Ventures, a venture capital firm.

That number could grow, of course, if generative AI becomes a more useful tool that we naturally use in everyday life. I suspect the humble web browser will open that path forward.

{Categories} {/Categories}
{URL}https://indianexpress.com/article/technology/artificial-intelligence/is-ai-the-future-of-web-browsing-10123158/{/URL}
{Author}unknown{/Author}
{Image}https://images.indianexpress.com/2025/05/may-11-18.jpg{/Image}
{Keywords}Artificial Intelligence,Technology{/Keywords}
{Source}POV{/Source}
{Thumb}https://images.indianexpress.com/2025/07/Tech-feature-images1.jpg{/Thumb}

Each week, the Law.com Barometer newsletter, powered by the ALM Global Newsroom and Legalweek brings you the trends, disruptions, and shifts our reporters and editors are tracking through coverage spanning every beat and region across the ALM Global Newsroom. The micro-topic coverage will not only help you navigate the changing legal landscape but also prepare you to discuss these shifts with thousands of legal leaders at Legalweek 2026, taking place from March 9-12, 2026, in New York City at the North Javits Center. Registration will be opening soon.

{Categories} {/Categories}
{URL}https://www.law.com/2025/07/11/law-firms-legal-tech-providers-embrace-agentic-ai-at-record-pace/{/URL}
{Author}Law.comRhys Dipshanhttps://feeds.feedblitz.com/-/921525869/0/law/legal-news.jpgArtificial Intelligence/Innovation/Legal Technology{/Author}
{Image}https://k2-prod-alm.s3.us-east-1.amazonaws.com/brightspot/58/37/38efd8a84ee8a59589d4f8922200/ai-law-jpeg767x505.jpg{/Image}
{Keywords}{/Keywords}
{Source}Implications{/Source}
{Thumb}{/Thumb}

It started with a strange disconnect.

Everywhere I looked—LinkedIn, podcasts, Slack threads—people were talking about AI. Loudly. Constantly. But in real terms? I saw very few people using it in any meaningful way. Maybe they logged into ChatGPT to punch up some marketing copy. That was about it.

I was hitting networking events with local execs and marketers. The tone was familiar: vague concern, low energy, and almost no hands-on experience.

One moment stands out in my memory of observing this disconnect. A work friend had just returned from SXSW, having gone to every AI session they could find. But when I asked if they’d used a Custom GPT, they blinked. Hadn’t even heard of it.

Everyone sounded exhausted by AI — while barely touching it.

4 Traps That Keep Teams from Getting Started
Looking back, I think there were four factors contributing to this gap between AI awareness and AI adoption. I saw these same dynamics play out in my team’s behavior as well as my own. Here’s what I observed:

1. Treating AI Like It Can Wait
This was our first mistake. We knew AI was important, but it never felt urgent. We weren’t sure what it was good for. Plus, as a people-leader, I didn’t want to foist confusing tools on a team already stretched thin.

2. Trying AI Once, Then Stalling Out
The next trap: doing one shiny thing and calling it a day. Someone shows you how to brainstorm blog titles or write a better LinkedIn headline, and that becomes your one AI trick.

But that’s not adoption.

3. Getting Derailed by Tool Hype
This one is probably the single greatest contributor to AI inaction. AI-related content (I’m looking at you, LinkedIn) is a firehose, and most of it’s driven by incentives to sell from SaaS products with AI features. If you’re perusing the AI tool marketplace, it’s easy to feel like you need a 12-tool stack just to keep up.

But if you limit yourself to just one paid LLM account, you can get all the mileage you need for your first 6+ months of AI adoption.

4. Fear of Change, Masquerading
There’s a more subtle blocker I’ve noticed — one that’s harder to call out because it often sounds principled. It’s the person who says:

“I’m just not comfortable with AI because of the ethical issues.”

“It’s trained on stolen data.”

“I don’t want to support a tool that might displace people’s professions.”

These are valid concerns. I share many of them. AI’s business models, energy consumption, impact on workers, and IP theft should be scrutinized.

But here’s what I’ve learned: sometimes those concerns are real, and sometimes they’re a mask for something else — fear of change. Dealing with the negative externalities of AI is something we need to face as a society. But as practitioners, we should reflect on how to separate these concerns from an honest appraisal of our own change aversion.

The Approach That Actually Worked
At work, my team and my own AI use went from a culture reflecting all of these blockers to one that enthusiastically gained curiosity as a group. AI adoption went from a nagging anxiety to the professional development highlight of my team’s year. What moved the on my team needle wasn’t flashy. It was a few grounded practices, repeated.

Weekly Time, with Permission to Play
I block an hour every Thursday morning for AI content consumption and experimentation. I encourage my team to do the same. It’s when I’m alert but open to distraction. I might watch a video from Marketing Against the Grain, test a new GPT, or tweak a prompt I saw on LinkedIn.

Some of it’s great. Some of it’s noise. But every week, I bring back something—an idea, a question, a clearer sense of what these tools are actually good for.

Testing on Practical Applications—In and Out of Work
Rather than trying to create new capabilities on the team, we focused our experimentation on using AI to alleviate annoying tasks at work and at home.

One teammate built a Custom GPT to turn messy client interviews into clean case study drafts. It now saves us four hours per piece. Another teammate started her AI journey with a packing list for a family trip. That grew into a work event-planning Chat GPT process. Now she reaches for AI instinctively.

What I want to encourage is the development of the instinct around when AI might be useful… and also when it’s totally unhelpful!

Making It Social
Once every two weeks, my team gets together and we create space for one person to demonstrate a new use of AI or a new tool they’re getting value from. Our show-and-tells are casual. Someone tried a new workflow that saved them time and uncovered new insights. Someone else hit a wall after getting excited about the value of Deep Research. We talk about both.

Our most junior teammate turned out to be our boldest experimenter. She had no old habits to unlearn, and no fear of the unknown. These are great assets in building AI curiosity.

The Real Shift: A Culture of Curiosity
The change isn’t just in what we use. It’s how we think. There’s pride in a clever prompt. There’s confidence in asking, “Could AI help with this?” And, there’s a growing sense that we’re not just watching the wave—we’re surfing it.

That’s because using AI well takes skill: framing, judgment, creativity. The tools don’t replace those things. They reward them.

The shift I’m proudest of? We treat AI like a puzzle. How do we cut the grunt work without lowering quality? Where can we trust it? Where should we double-check?How do we stay human in the loop?

There are no final answers, just better questions. And slowly: better, more satisfying and interesting work.

One Step to Start
If AI feels overwhelming, don’t start by researching the best new tools. Start with your calendar. Block one hour. Pick one tool. Use it on something you already need to do. See what happens.

If it works, share it. If it flops, share that too. AI doesn’t need to be a strategy. It can be a habit.

The post How to Kindle an AI-Curious Culture in Your Team appeared first on Atomic Spin.

{Categories} {/Categories}
{URL}https://spin.atomicobject.com/ai-curious-culture/{/URL}
{Author}Elaine Ezekiel{/Author}
{Image}{/Image}
{Keywords}Artificial Intelligence,culture,artificial intelligence{/Keywords}
{Source}Inspiration{/Source}
{Thumb}{/Thumb}

zuperia/Getty ImagesAI search start-up Perplexity has ramped up its competition with Google by releasing Comet, its new web browser, on Wednesday.
Built upon Perplexity’s proprietary search engine, Comet is compatible with "all of your usual extensions, settings, and bookmarks," according to a Perplexity blog, meaning it’s "a seamless switch" to make it your new default browser. It’s initially being launched for Mac and Windows, with support on other platforms expected to arrive in the coming months. 

Also: Perplexity joins high-powered, high-priced AI race – here’s everything ‘Max’ includes
Perplexity CEO and cofounder Aravind Srivinas wrote on X Thursday morning that Comet would be available on Android devices soon. 
"Comet reimagines the browser from the ground up," Perplexity wrote on its website. "It actively helps you ask, understand, and remember what you see. It connects the dots at lightning speed and assists with distracting tasks that steal your focus."

In the spirit of collaboration, Comet comes with its own AI agent, Comet Assistant, which is integrated directly into the browser and upon which users can offload a variety of simple and mundane tasks. 
Also: How to install Perplexity AI’s app on Linux (I found an easier way)
You can ask the agent to go through your unread emails in the morning, pull out the messages from your coworkers, and provide a quick summary of each. That requires, of course, handing over your email data to Perplexity; the same goes for your personal calendar, notes app, or anything else you’d like Comet Assistant to be able to interact with and extract information from. 

It’s a good idea to review your workplace’s AI policy, if it has one, or check with a superior before leaking any potentially sensitive information to Perplexity or any other chatbot.
Comet is currently available to subscribers of the company’s $200-per-month premium service, Perplexity Max, and to a cohort of early users who were invited after joining a waitlist. 
A new era of AI-powered search Launched in 2022, Perplexity’s search engine leverages a collection of large language models (LLMs) to respond to user queries with AI-generated summaries, links to sources, and suggestions for follow-up questions. The company has marketed itself as the next phase in the evolution of online search, with the long-term goal of usurping the dominant model, pioneered by Google, of responding to user queries with a list of relevant web links.

Also: I tried Perplexity’s assistant, and only one thing stops it from being my default phone AI
At the same time, however, Google is building a new future of Search with its controversial AI Overviews and the more recently released AI Mode, which operates a lot like Perplexity. Meanwhile, executives at Apple, have reportedly floated the idea of buying the up-and-coming AI search start-up, potentially to improve Safari. 

Even with the launch of its new web browser, which will compete with the likes of Google Chrome and Safari, Perplexity has a long way to go before it replaces Google as the default search engine for the majority of the population. 
Google’s model has been inimical to exploration and learning, according to Perplexity: "the web — our greatest source of information — was never designed to nurture curiosity; instead we’ve been asked to ‘browse’ it through a one-way lens," the company says on its website. The implication, of course, is that the company’s new model of web search represents a collaboration between humans and AI, both actively engaging one another to ask deeper questions and discover new knowledge.

Also: Google’s AI Overviews will decimate your business – here’s what you need to do
Still, the online search industry’s accelerating drift towards generative AI strongly suggests that the strength of Perplexity’s position will only continue to grow over time. 

{Categories} {/Categories}
{URL}https://www.zdnet.com/article/perplexitys-comet-ai-browser-is-hurtling-toward-chrome-how-to-try-it/{/URL}
{Author}unknown{/Author}
{Image}https://www.zdnet.com/a/img/resize/ab7a049ecb0275adf4c10827eee8b43920f9b185/2025/07/10/af4bc150-2780-478f-b2ce-969f7c54d5c4/gettyimages-1344634113.jpg?auto=webp&fit=crop&height=675&width=1200{/Image}
{Keywords}{/Keywords}
{Source}Inspiration{/Source}
{Thumb}{/Thumb}