doctor can practice for 30 years and get sharper every year. A hospital can see millions of patients and barely improve at treating the next one.
Ali Khokhar lost his mom to breast cancer after her lump was dismissed twice.
Concurrence is building the systems so healthcare organizations actually learn from every case they see and that learning reaches the next patient who needs it.
The clinicians still make every call. The system just stops forgetting.
When I was 13, I lost my mom to breast cancer. I still wonder if it could have been prevented.
When she found the lump, she did everything right.
She went to her primary care doctor, and he told her it was nothing. My mom wasn’t convinced, so she went to a women’s health specialist for a second opinion and was told the same thing. A year passed before she saw a third doctor who was shocked that nothing had been done and ordered tests the same day.
By the time she was diagnosed, the cancer had already spread.
For the next three years, she went through chemo, surgery, and radiation. Specialist after specialist, asking the same questions again and again.
After she passed away, there were two thoughts I couldn’t out of my head:
(1) Somewhere, a doctor must have seen a case like my mom’s and caught it early.
(2) Nothing that doctor learned had any way to reach her.
Healthcare runs in my family. All four of my sisters are nurses or pharmacists, and my fiancée spent the pandemic working in a multi-organ transplant recovery ward.
I’ve seen how hard clinicians work, and how much of that work requires understanding the patient and recognizing patterns from past cases.
That’s why a doctor can practice for 30 years and get better every year, while a hospital can treat millions of patients without getting much better at treating the next one.
What’s missing in healthcare is the infrastructure for it to learn from its own experience. If we don’t examine the cause and outcome of every interaction, how do we get better at knowing which signs to watch for?
I spent years at Google and Upwork building AI from human expertise, then eventually left big tech to work on the one problem I couldn’t stop thinking about.
I started a company called Concurrence (@concurrencehq) and raised $24M to build data and AI systems that enable healthcare orgs to learn from every patient they treat. Nothing learned is lost, and it reaches the next patient who needs it.
We’ve already supported care for over 10 million patients worldwide.
My mom deserved a doctor who had seen her case a thousand times. Every patient does.
When I was 13, I lost my mom to breast cancer. I still wonder if it could have been prevented.
When she found the lump, she did everything right.
She went to her primary care doctor, and he told her it was nothing. My mom wasn’t convinced, so she went to a women’s health specialist for a second opinion and was told the same thing. A year passed before she saw a third doctor who was shocked that nothing had been done and ordered tests the same day.
By the time she was diagnosed, the cancer had already spread.
For the next three years, she went through chemo, surgery, and radiation. Specialist after specialist, asking the same questions again and again.
After she passed away, there were two thoughts I couldn’t out of my head:
(1) Somewhere, a doctor must have seen a case like my mom’s and caught it early.
(2) Nothing that doctor learned had any way to reach her.
Healthcare runs in my family. All four of my sisters are nurses or pharmacists, and my fiancée spent the pandemic working in a multi-organ transplant recovery ward.
I’ve seen how hard clinicians work, and how much of that work requires understanding the patient and recognizing patterns from past cases.
That’s why a doctor can practice for 30 years and get better every year, while a hospital can treat millions of patients without getting much better at treating the next one.
What’s missing in healthcare is the infrastructure for it to learn from its own experience. If we don’t examine the cause and outcome of every interaction, how do we get better at knowing which signs to watch for?
I spent years at Google and Upwork building AI from human expertise, then eventually left big tech to work on the one problem I couldn’t stop thinking about.
I started a company called Concurrence (@concurrencehq) and raised $24M to build data and AI systems that enable healthcare orgs to learn from every patient they treat. Nothing learned is lost, and it reaches the next patient who needs it.
We’ve already supported care for over 10 million patients worldwide.
My mom deserved a doctor who had seen her case a thousand times. Every patient does.
The markup problem in AI video has been hard to ignore for a while. Routing costs keep climbing while the interesting work is supposed to happen higher up.
Sume’s framing is the part that stands out: treat the infrastructure layer as a commodity so builders can put more of their budget into the actual products and experiments. Whether the pricing holds up in practice is something people will test for themselves.
What feels right is the direction less tax on access, more room at the application layer.
That’s the version of the stack worth building toward.
As a builder in the AI video space, I was terrified about how much markup API providers charge for simply routing the models.
Higgsfield API adds a 40% markup even with its maximum advertised discount. Fal adds 100%. Runway adds 414% (Seedance 2 480p)
I might be hated by the industry, but :
Today, we’re launching Sume API, the first image & video model provider with 0% markup.
For example with Seedance 2.5 1080p
• 50% cheaper than fal
• 50% cheaper than higgsfield api (29% even with biggest discount)
• 28.02% cheaper than kie ai
The routing infrastructure layer is never the moat. We believe that APIs should be commoditized, and the moats will be built at the application layer.
Check the pricing comparisons below, and see how the broken industry is saved.
As a builder in the AI video space, I was terrified about how much markup API providers charge for simply routing the models.
Higgsfield API adds a 40% markup even with its maximum advertised discount. Fal adds 100%. Runway adds 414% (Seedance 2 480p)
I might be hated by the industry, but :
Today, we’re launching Sume API, the first image & video model provider with 0% markup.
For example with Seedance 2.5 1080p
• 50% cheaper than fal
• 50% cheaper than higgsfield api (29% even with biggest discount)
• 28.02% cheaper than kie ai
The routing infrastructure layer is never the moat. We believe that APIs should be commoditized, and the moats will be built at the application layer.
Check the pricing comparisons below, and see how the broken industry is saved.
Less time staring at a blank canvas. More time bringing ideas to life. Start with AI-generated assets from Dreamina, then edit your marketing content in CapCut PC.
This creative workflow is available for just $6.29 with the limited-time offer.
Available for a short window: October 20–30.
#CapCutDidThat #Dreamina #Smallbusinessmarketing #CapCutSale
CapCut Pro is 60% OFF and Ultra is 40% OFF, too! Oct 20–30, exclusively on CapCut Desktop.
Tesla Roadster hype deserves a video that hits just as hard. With CapCut PC, you can turn a collection of Roadster clips into a trend-ready edit without letting the footage feel like a random montage.
Line up your best shots on the multi-track timeline, trim out the slow moments, and sync your cuts with the soundtrack. Add punchy transitions to make every reveal feel intentional.
Got the clips? Give the Tesla hype your own creative spin with CapCut PC.
#capcutpc #capcutmarketing #capcutsale #capcutblackfriday
Most AI tools give you the same purple gradient, Inter font homepage.
I opened MiniMax Code, did the daily check-in (400 free points), then used the Frontend Design skill.
Prompted it: “Design a distinctive visual direction for this product homepage and implement it responsively.”
unique typography, a clear point of view, intentional layout and then write the actual responsive code. Not the usual AI template. It also used Computer Use where it needed to check the result in a real browser window.
Then I stepped away. From my phone (Remote Control) I checked progress and approved the next step while it kept going on my computer.
Points stack to 4000 for a full week of check-ins (valid 30 days). Enough to properly test real frontend work without paying.
If you want an agent that can actually design and ship distinctive frontends, start with the daily check-in + the Frontend Design skill.
#MiniMaxCode
best software never asked you to meet it midway. It met you where the work already lived.
30 yrs we all spent that care turning raw information into something you could feel.
Then the most capable software ever built handed us a text box and called it progress.
OpenUI 1.0 is the quiet correction.
Not another generic chat surface. Interfaces that form around the actual job, a map, dashboard and comparison, built from the same components that already make a product feel like itself.
The intelligence is here. The interface is finally catching up.
For 30 years, technology has moved in one direction: turning information into intuitive interfaces
Somehow, the smartest software we’ve ever built took us back to a textbox
We’ve spent the last 2 years at @openuidev trying to fix that. 6 months ago we open-sourced it: 10K+ GitHub stars, 6M+ downloads
ChatGPT shipped Intelligent UI and showed everyone what it looks like
Today we’re releasing OpenUI 1.0 bringing it to every other agent
For 30 years, technology has moved in one direction: turning information into intuitive interfaces
Somehow, the smartest software we’ve ever built took us back to a textbox
We’ve spent the last 2 years at @openuidev trying to fix that. 6 months ago we open-sourced it: 10K+ GitHub stars, 6M+ downloads
ChatGPT shipped Intelligent UI and showed everyone what it looks like
Today we’re releasing OpenUI 1.0 bringing it to every other agent
Sleep is now part of the dev loop.
The setup in the animation is simple. The coding agent works through the night, and its definition of done is that TestSprite's Integration Tests pass against the running app. Each failure comes back as the step that broke plus a fix prompt the agent can act on, so it fixes and retests on its own instead of stopping to wait for you.
The CLI is open source under Apache-2.0 and works with Claude Code, Codex, Cursor, Antigravity, Kimi and Trae.
Introducing our new AI model @trydrama_io to kill reshoots and make acting editable!
Control what part of a performance to preserve and what part to change using a simple intensity slider.
We just nailed 3 industries(thread):
Introducing our new AI model @trydrama_io to kill reshoots and make acting editable!
Control what part of a performance to preserve and what part to change using a simple intensity slider.
We just nailed 3 industries(thread):
Rewriting your resume from scratch for every single job application doesn’t have to be your full-time job.
I can feel my buddies frustration in replies all the time.
This 𝐟𝐫𝐞𝐞 𝐥𝐢𝐯𝐞 𝐆𝐏𝐓 𝟔 𝐀𝐬𝐭𝐫𝐚 𝐂𝐫𝐚𝐬𝐡 𝐂𝐨𝐮𝐫𝐬𝐞 has attendees build their own Astra workflows during the session.
You learn prompts that get Astra to nail the output on the first try while using fewer tokens, then watch it find roles that match you and tailor your resume for each one.
Everyone who signs up also gets the Astra Power Playbook with ready prompt formulas and workflows.
Sign up: https://t.co/Sr2uLoivkN #AIWorkflow
@DynaRobotics Honestly, we daily saw edited 10 - 20 second clips of robots folding one shirt perfectly. Watching continuous workflow without those awkward mechanical stops is eye catching
unpopular opinion: the future of AI isn't one genius assistant per person. it's a group chat where people and their agents work things out together. teamily bet on that long before dots