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🚨BREAKING: • Viktor hit $20M annualized revenue run rate before a single Microsoft Teams user could access it. As of today, they can. Teams users, welcome. Not another chatbot in the sidebar. Not Copilot waiting for a prompt. An actual employee you can @ mention in any channel —...

142,928 views • 2 months ago •via X (Twitter)

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Possibly the biggest change in Microsoft Teams history? Teams without the Teams? Public preview in November to desktop, mobile, iOS, and Android. Here is what you need to know: 🟣 Microsoft is introducing a new combined chat and channels experience. Meaning chat and teams/channels will show up under the "Chat" sidebar icon. No more dedicated Teams sidebar button. 🟣 Teams and Channels will have their own section in chat. 🟣 Group your chats and/or channels however best works for you with favourites and custom sections (up to 50 sections and 50 items per section) 🟣 “Unread,” “Chat,” “Channels,” “Meetings,” and “Muted” Filters 🟣 New message can initiate a new chat or new channel post 🟣 New Mention view gathers all your mentions into a single interactive list. 🟣 At launch, a self-service, guided onboarding will help users discover the new experience and configure it to their preferences (on or off) 🟣 Users who prefer to keep chat and channels separate can easily do so during the onboarding process or at any time later. So far, it looks like there are no IT/tenant-level override controls. This experience change is targeted at getting more users using teams/channels. Most Teams users live in "chats", not teams/channels. There will undoubtedly be some pushback from users who use teams/channels well and like having the mental separation of teams/channels vs chats. I've been fortunate to be using it for a while, and I'm personally a big fan; my use of the correct channels has gone way up, and now I can find them all in one place in the app, particularly on mobile. I'm now much more likely to see channel conversations I need to see. What do you think? #MicrosoftTeams #Microsoft365

Tom Arbuthnot

64,542 views • 1 year ago

15 AI tools researched, ranked, and turned into X-ready content in ~2 minutes. I gave Viktor one job: Find the best new AI tools for our audience, research them, rank the top 3, and turn the research into X-ready content. In about 2 minutes, Viktor ran 24 targeted searches, researched 15 tools, cross-checked pricing, scored the options, built the comparison, and produced the final post. My first attempt didn't work. The workflow stalled before Viktor could connect the research and content steps. Then I adjusted the task, and that's when things clicked. What surprised me wasn't that he could research. It was how much of the workflow he could actually handle. Research. Compare. Prioritize. Create. Instead of jumping between tabs, collecting information, comparing tools, and turning research into content manually, Viktor handled the workflow in one place. That's the part I think people miss about AI employees. The value isn't another chatbot that gives you an answer. It's having an AI teammate that can take on real work and fit into the way your team already operates. Viktor works inside Slack and Microsoft Teams and connects to 3,200+ tools. A copilot helps you work. An AI employee works when you don't. I think this is where AI employees get genuinely interesting: the question isn't whether they can answer you, but whether you can trust them with actual work. Hire Viktor for your team. $100 in credits included, no card. Full link in first comment. #AIemployee #AITeams Paid Partnership

Marry Evan

29,470 views • 3 days ago

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.

Score

11,292 views • 11 days ago