Topic
20 articles found
Tech Mahindra CEO Mohit Joshi's pay surged 11.7% to Rs 67.5 crore in FY26, surpassing peers at Wipro and TCS. This reflects the company's aggressive push into AI and its ongoing turnaround strategy. While median employee pay dipped, Tech Mahindra reported strong revenue and profit growth, with signi
India is actively seeking semiconductor investments and multilateral funding at the Pax Silica summit in Washington D.C. The nation aims to leverage the US's $250 million seed fund to bolster its growing semiconductor manufacturing and design capabilities. This initiative is part of a broader global
The central government could end up with a 1-2% stake in AI startup Sarvam, valued at $1.5 billion, as part of its $300 million funding round. This rare instance of equity holding arises from non-cash support provided under the IndiaAI Mission, where the government offered compute infrastructure in
Cybersecurity faces a monumental opportunity and challenge with advanced AI models now identifying software flaws at lightning speed. Zscaler CEO Jay Chaudhry highlights that vulnerabilities hidden for decades are being uncovered, demanding rapid fixes before exploitation. The company is actively te
All the ways to watch Czech Republic vs Mexico, as the European nation attempts to join the tournament co-hosts in the World Cup round of 32.
Changing this simple setting keeps my Pixel chilled out
Save $200 on MSI's Katana 15 HX during Prime Day. It houses an Intel Core i7 CPU, RTX 5060 GPU, and a 165Hz QHD display.
The official Prime Day 2026 sale is now flying, and the AirPods deals are too. The new 2026 AirPods Max 2 are now sitting down at a wild $150 off the list price in all five colors, while AirPods Pro 3 are nearly 30% off, and we are still tracking AirPods 4 down at $99 shipped. AirPods Pro 3 $179 (Re
Two significant commits hit submain today, closing out the static string subset for the JIT. D2.3d brings print-time string interpolation and f64 print support, and D2.3c adds compile-time literal string concatenation and content equality. The commit sequence moved our parity numbers from 215/71/0 t
3 Reasons Your AI Loop Stopped Working (None of Them Are the AI's Fault) You built a loop. It ran. You felt like a genius. Then you checked back two days later. The loop was dead. The output looked weird. You spent 20 minutes fixing things, ran it again, and by day four the whole thing was collectin
Hey Dev Community, If you are running enterprise-scale web scrapers, pricing monitors, or data ingestion pipelines for LLMs, you’ve probably spent sleepless nights dealing with network latency and sudden 403 blocks. When choosing an infrastructure partner, every provider pitches the same script: "99
Introduction In the early 2000s, email spam was rampant, cluttering inboxes with unsolicited messages promising quick riches or promoting dubious products. Fast forward to today, and a similar phenomenon is occurring in the world of open-source software: Pull Request (PR) spam. Much like its email p
Part 2 of the Building Enterprise AI Automation Systems Series Introduction One of the biggest obstacles in enterprise AI is not choosing a model. It is finding data. Most tutorials assume that training data already exists. Reality is very different. Large organizations rarely share operational data
If you've ever watched a hacker movie and seen someone plug in a USB and own a machine in seconds — that's not Hollywood magic. That's a Rubber Ducky. And I built one for under ₹150. What Even Is a Rubber Ducky? What I Used DigiSpark ATtiny85 — ₹120–150 on Amazon India That's it. No soldering. No sp
Part 3 of the Building Enterprise AI Automation Systems Series Introduction Named Entity Recognition (NER) is one of the oldest problems in Natural Language Processing. Most tutorials introduce NER using examples like: Person Organization Location Date A sentence such as: Elon Musk founded SpaceX in
Introduction Most developers today are learning how to “use AI APIs.” But that’s not enough anymore. The real shift happening in software engineering is this: We are moving from building APIs → to building AI-powered systems. And that requires a completely different mindset. Most tutorials show this
Apache Iceberg looked like the answer to everything when we first adopted it. Open format, ACID transactions, time travel, schema evolution. We migrated our Hive tables, ran a few queries, and felt good about life. Three months later, our S3 costs doubled. Queries that used to take 10 seconds were t
Part 4 of the Building Enterprise AI Automation Systems Series Introduction Most Named Entity Recognition (NER) tutorials end with a prediction. The model successfully extracts: COMPANY INVOICE CONTRACT PURCHASE_ORDER The article ends. The notebook prints a beautiful JSON response. Mission accomplis
You forwarded the phishing email to the security channel about ninety seconds too late. The laptop is already cooperating with someone else. Your personal access token, the one you minted "just for that one script", is on its way to whatever Discord pays for stolen tokens this week. Now what? For us
Thariq Shihipar, engineering lead for the Claude Code team, recently published a blog post (Using Claude Code: The Unreasonable Effectiveness of HTML) arguing that HTML, with its richer visualizations, color, and interactivity, improves the productivity of human-agent communication in many settings,
