๐ง๐ฒ๐ ๐-๐ผ๐ป๐น๐ ๐๐ ๐ถ๐๐ปโ๐ ๐ฒ๐ป๐ผ๐๐ด๐ต ๐ฎ๐ป๐๐บ๐ผ๐ฟ๐ฒ.
Modern intelligent systems can now understand images, voice, and video all at once. They go beyond processing data, they actually make sense of real-world context.
#IoTric#GenerativeAI#MultimodalAI#AIInnovation
Behind every โquick update,โ every โsmall change,โ and every โjust one last taskโโฆ thereโs a hardworking person making it all happen. ๐
๐ช๐ถ๐๐ต๐ถ๐ป๐ด ๐ฒ๐๐ฒ๐ฟ๐๐ผ๐ป๐ฒ ๐ฎ ๐๐ฎ๐ฝ๐ฝ๐ ๐๐ฎ๐ฏ๐ผ๐๐ฟ ๐๐ฎ๐!
#LabourDay#WorkLife#Teamwork#Gratitude#KeepBuilding
โItโs just an MVP, it doesnโt have to be perfect.โ
โ Myth: MVP means launching something buggy, unfinished, or poorly designed
โ Fact: MVP means focused, not crappy
You are not building everything, but whatever you build should work properly and solve a real problem
Ideas donโt kill your MVP.
Overbuilding does.
Most founders donโt fail because their idea is badโฆ
they fail because they take too long to launch.
They try to build ๐ฒ๐๐ฒ๐ฟ๐๐๐ต๐ถ๐ป๐ด and end up launching nothing.
Let's do it. https://t.co/LjYjSy3gDh
๐ช๐ต๐ฎ๐ ๐ถ๐ณ ๐น๐ฎ๐๐ป๐ฐ๐ต๐ถ๐ป๐ด ๐๐ผ๐๐ฟ ๐๐๐ฎ๐ฟ๐๐๐ฝ ๐ฑ๐ถ๐ฑ๐ปโ๐ ๐๐ฎ๐ธ๐ฒ ๐บ๐ผ๐ป๐๐ต๐...
but just one focused week?
At iotric, we frequently witness the effectiveness of a targeted Minimum Viable Product (MVP) approach.
https://t.co/LjYjSy3gDh
๐๐ ๐ท๐๐๐ ๐ต๐ฒ๐น๐ฝ๐ฒ๐ฑ ๐ฑ๐ถ๐๐ฐ๐ผ๐๐ฒ๐ฟ ๐ป๐ฒ๐ ๐ฝ๐ต๐๐๐ถ๐ฐ๐
Why this is big:
โข AI isnโt just analyzing data, itโs helping discover theory
โข Complex physics โ simpler formulas
โข A real example of AI + scientists = new knowledge
#AIinScience#TheoreticalPhysics#GPT52
A Curious Way to Measure Reputation
We know what people say about us. "Hotbed for extremism." "Dangerous." "Fringe."
We'd like to have a more honest conversation about how those judgments are made.
What we actually do:
We don't algorithmically manipulate what you see. Objective criteriaโviews, likes, subscribersโdetermine what's prominent. We don't optimize for engagement regardless of consequence.
We don't sell your data. We let you opt out of advertising entirely. We honor data subject access rights regardless of jurisdiction. We believe privacy is a fundamental human right.
We're transparent about moderation decisions and provide appeals. We joined the UN's Tech Against Terrorism partnership in 2020. We publish transparency reports.
We restrict our platform to adults. We don't target children.
What gets you labeled "legitimate":
Meta earns $3 billion annually from ads it internally classifies as scams, illegal gambling, and banned content. When a specialized anti-fraud team cut problematic ads in half, leadershipโfollowing direction from the topโdisbanded the team entirely. They set a "guardrail" limiting how much revenue they're willing to forgo for anti-scam efforts: 0.15%.
Facebook was the primary platform for 495 verified hate speech events in India in 2024. Of 259 instances of dangerous speech including explicit calls for violence, Facebook hosted 164. As of February 2025, 98.4% remain online despite clear violations of their own community standards.
Facebook removes 7 million pieces of hate speech content per quarterโwhich tells you something about the volume present on a platform considered mainstream and respectable.
The company that does this meets with presidents. Sits at the table for conversations about AI safety. Is treated as a pillar of the technology establishment.
The double standard:
We host some content that was removed from other platforms. Some of it is objectionable. We don't deny this.
But here's what's curious: the metric for "dangerous" seems to be concentrationโwhat percentage of a small platform's content is problematic. Not scaleโhow many millions of people are actually exposed to harmful content. Not business modelโwhether a platform structurally profits from harming users. Not intentโwhether leadership knowingly protects harmful revenue streams.
By concentration, a small platform hosting 10,000 problematic videos is "a hotbed for extremism."
By scale, a platform hosting millions of pieces of hate speechโwith 98% of documented dangerous speech remaining onlineโis "struggling with content moderation challenges."
By business model, a platform that doesn't manipulate users or sell their data is suspect. A platform that knowingly extracts billions from scams targeting ordinary people is mainstream.
By intent, a platform working with Tech Against Terrorism is fringe. A platform that shut down its own anti-fraud team to protect scam revenue is respectable.
What we're asking for:
Not a pass. Not an exemption from criticism. We know we host content many find objectionable, and we accept that criticism comes with our commitment to free expression.
What we're asking for is consistency.
If the concern is harm to users, then a platform knowingly profiting from fraud at massive scale should face more scrutiny than a platform that doesn't algorithmically manipulate anyone.
If the concern is extremist content, then absolute numbers matterโnot just percentages. A platform where millions encounter hate speech is a larger vector for radicalization than a platform with 11 million monthly users total.
If the concern is protecting vulnerable people, then a platform that targets everyone including children with engagement-maximized content should raise more alarms than one restricted to adults with no algorithmic manipulation.
We're not asking to be celebrated. We're asking why the platforms that respect user privacy, don't sell data, don't algorithmically manipulate, and don't profit from fraud are labeled dangerousโwhile platforms that do all of those things are labeled legitimate.
That's a curious way to determine reputation.
We think it deserves a more honest conversation.
https://t.co/yskRX1lGx8
๐๐ก๐ง๐-๐๐จ๐ง๐ข๐ ๐๐ง๐๐ข๐ก
We love asking โsmartโ questions like:
โ Can AI handle this?
โ Should we automate this?
โ Whatโs our deflection rate?
๐๐๐ ๐ต๐ผ๐ป๐ฒ๐๐๐น๐?
If thatโs your entire strategyโฆ youโve already missed the point.
Thatโs not innovation.
Thatโs just replacing people with bots and hoping it magically counts as progress.
Hereโs what actually matters:
Your data is already telling you where users struggle.
You donโt need more questions โ you need better answers.
Stop obsessing over what to automate.
Start digging into why people need help in the first place.
โ โEveryone drops off when pricing shows upโฆ maybe we need to address their doubts, not just flash numbers.โ
โ โPeople are engaging but still not getting answers. Where exactly does hope turn into frustration?โ
โ โSupport sees the same issue every day. What if we solved it before users even have to ask?โ
When you understand whatโs breaking, you can fix what actually matters.
Thatโs how you genuinely help people.
Thatโs how you build something people truly want to use.
The Employee That Never Sleeps
In today's digital-first world, your website is often the first impression potential clients have of your business. It works 24/7, never takes a day off, and represents your brand to thousands of visitors.
At iotric, we don't just build websites โ we create powerful digital sales tools that:
1. Convert visitors into customers
2. Showcase your brand's unique value
3. Drive measurable business results
4. Work tirelessly to grow your business
Your website should be doing more than just existing online. It should be your most productive team member.
Reach out: https://t.co/5r0i7AjZ3j
AGI โ the big dream of AI. But what are we really building toward?
At its core, a generative AI agent is pretty straightforward: it's software that observes, thinks, and acts using whatever tools it has available, all to reach a goal you set for it.
But here's the thing we need to remember: humans aren't going anywhere.
We talk a lot about "AI transforming everything," and sure, it's powerful. But the real magic happens when we understand how these systems think and solve problems, and then use that knowledge to stay in control.
The future isn't AI replacing us. It's Human + AI, working together. And for that to work well, we need to stay at the forefront. We set the goals. We make the calls. We decide what matters.
#AI #GenerativeAI #AgenticAI #AGI #ArtificialIntelligence #FutureOfWork #TechExplained #AITools #DigitalTransformation #LearnAI #AIEducation #ProductivityWithAI #HumanFirst #Upskill2025
BUILDING BETTER
Top-performing product teams aren't just coding faster. They're learning smarter. Here's how:
1. They steal the best patterns from products that work
2. They spot where MVPs fail โ and pivot before it's too late
3. They ask for feedback (and actually build with it)
4. They treat every sprint like a learning lab
With iotric, it's not guesswork. You get real expertise from real product journeys โ so you can ship faster, build smarter, and deliver products that matter.
Great products aren't lucky. They're engineered.
And you're already on your way.
What if you could validate your product idea before investing millions?
That's exactly what forward-thinking founders are doing with iotric's MVP Development approach โ turning concepts into testable products and reducing risk at every stage.
See how successful startups are:
1. Launching MVPs that secure funding and early adopters
2. Scaling from single-feature products to full-scale platforms
3. Building with Web3, IoT, AR/VR, and cutting-edge tech
It's building the right product, faster.
:point_right: Learn how: [https://t.co/fA19VQfDGF]
The Browser War Just Got Intelligent
OpenAI just rolled out something interesting.
ChatGPT Atlas, a browser that works differently than what we're used to.
Instead of clicking around and searching through multiple tabs, you can just ask it what you need in plain language. Looking to compare some options? Need to pull data from a report? Just ask, and it helps you out.
It's part of a bigger wave where Perplexity and Microsoft are building similar AI browsers too. Looks like the way we browse and work online is changing pretty quickly.
Worth keeping an eye on how this evolves!