Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.
It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
Introducing Claude Design by Anthropic Labs: make prototypes, slides, and one-pagers by talking to Claude.
Powered by Claude Opus 4.7, our most capable vision model. Available in research preview on the Pro, Max, Team, and Enterprise plans, rolling out throughout the day.
New Anthropic research: Emotion concepts and their function in a large language model.
All LLMs sometimes act like they have emotions. But why? We found internal representations of emotion concepts that can drive Claude’s behavior, sometimes in surprising ways.
4% of GitHub public commits are now made by Claude Code
and this number is rising exponentially, expected to reach 20% soon
(Doesn't even include Codex and other coding agents - so real number is larger)
A whole new breed of developers is rising silently in the background
Stack Overflow wasn’t just a Q&A site.
It was mentorship at scale.
AI didn’t replace learning — it changed how we learn.
Tools evolve. Curiosity stays.
#StackOverflow
A great visual positioning system makes augmented reality feel like magic... this tech helps your phone (or robot) figure out precisely where it is in 3D space.
Here's MultiSet AI nailing it in real-time, at night, and on-device too. This new reveal shader animation shows just how well it's working.
IMO this tech is slept on despite being key infrastructure for physical AI to actually work.
Introducing our AI co-scientist, a multi-agent AI system built with Gemini 2.0.
We think of it as a virtual collaborator for scientists, using advanced reasoning to synthesize a huge amount of literature, generate novel hypotheses, and suggest detailed research plans. We’re seeing promising early results in important research areas like liver fibrosis treatments, antimicrobial resistance, and drug repurposing. As a next step, we’re opening up a trusted tester program for scientists around the world.
Good news for Indian tech companies who use Google Maps APIs.
Google announces "India specific pricing" for Maps APIs, with up to 70% lower prices on most APIs.
In my 5 years at Swiggy, I never saw Google Maps drop their prices. Maps API billing moved in only one direction - up.
It's great to see competition drive prices lower for consumers. Kudos to @MapmyIndia
and @Krutrim for shaking up this monopoly.
When companies compete, consumers benefit.
https://t.co/EKKsPcQ1Ui
Hey #geospatial experts! As of the v1.2 release, Whitebox Workflows for Python (WbW) is free. WbW is a Python library for advanced geoprocessing, including more than 400 functions for #gis and #remotesensing analysis. WbW enables you to write powerful geoprocessing scripts. pip install whitebox-workflows #gischat #lidar #geonews #QGIS #arcgis #dataviz #python #mapping #Terrainanalysis #spatialanalysis #geomorphometry
For more info: https://t.co/BBMSMuzKT1
Linear Regression clearly Explained!
Linear Regression models relationship bitheen a dependant variable (y) & two or more independent variables (x1, x2 ...)
❗️ For the sake of simplicity we discuss linear regression with a single independent variable.
Mathematical Representation:
y=mx+c
where:
- y is the dependent variable
- x is the independent variable
- m is the slope of the line
- c is the y intercept
Cost Function:
❗️The goal is to find the best values for m and c that minimize the error between the predicted values & the actual values for all data points.
This is how the cost function looks, a mean squared error:
MSE= 1/N∑(yi−(m*xi+c))**2
Where:
- N is the number of data points.
- yi is the actual value for the ith data point.
- mxi+c is the predicted value for the ith data point.
How it works (Optimisation)❓
To minimize the MSE, we can use gradient descent.
The basic idea is to:
- Start with some initial value of m & c
- Compute the gradient of the MSE w.r.t. both m & c.
- Update m & c in the direction of the negative gradient.
Implementation from Scratch:
Now that we understand how things work it's fairly simple to implement linear regression in Python!
Check this out 👇
That's a wrap!
If you interested in:
- Python 🐍
- ML/MLOps 🛠
- CV/NLP 🗣
- LLMs 🧠
- AI Engineering ⚙️
Find me → @akshay_pachaar ✔️
Everyday, I share tutorials on above topics!
I also write a weekly Newsletter on AI Engineering, link in the next tweet!
Cheers!! 🥂
ShadeMap now calculates annual #solar insolation adjusting for shading from trees, buildings and other man made objects 😎
The amount of solar power available minute by minute is indicated by colors on the chart (🟦 low, 🟩 medium 🟥 high) and mousing over displays the kW amount
Ashwin said "Australia totally deceived me personally, I had a chat with George Bailey during the mid innings, I asked him why didn't you guys bat first like you always do - he answered back, we have played IPL & Bilateral series here a lot - red soil disintegrates but not black soil & it gets better under lights - no impact on dew on red soil but black soil has good turn in afternoon & then it will be a concrete in night - this is our experience". [Ashwin YT]
Last word
The Ahmedabad crowd was rubbish
Need proper fans inside a stadium instead of fly by night pretenders
Like the amazing people at Wankhede
Proper fans
Cheered the team on and especially Shami post the dropped catch
Chanted his name non stop
Boosted him and the team
Energised them
Lifted them when the Kiwis were looking ominous
Shami got 7 eventually
Last time out in Mumbai for a WC final, we won
Choose ur venues wisely
I just released a new tool! A command-line interface (CLI) that takes an AOI (as GeoJSON) and downloads all the buildings from @OvertureMaps or Google Open Buildings datasets to your computer, in the format of your choice (gpkg, shp, etc) Get it at https://t.co/l7pkjNg6Wf...