Latest news with #Python
Hans India
5 hours ago
- Business
- Hans India
KSRM College inks MoU with Innomatics
Kadapa: Innomatics Research Labs, Hyderabad, a fast-growing edtech company, has signed a key Memorandum of Understanding (MoU) with KSRM College of Engineering (Autonomous), Kadapa. The agreement aims to provide students with modern and essential technical training in data science, Artificial Intelligence (AI), mission learning, full stack development, Python, generative AI, Amazon Web Services (AWS), digital marketing, etc. Innomatics is already a leader in preparing students according to industry needs, and through this partnership, students will get project experience, expert guidance and industry-based training. The programme was attended by Dr Kandula Chandra Obul Reddy, Head of Kandula Educational Institutions, Principal VSS Murthy, Vice-Principal T N Prasad and Professor V Giridhar (Dean, Industries Cell). Special thanks was extended to Vamsi Krishna Kanagala, Regional Head, Innomatics, who played a key role in the success of this partnership.
United News of India
2 days ago
- Business
- United News of India
IIES: Best Embedded Systems & IoT Training Institute in Bangalore
Bangalore (Karnataka) [India], June 25: The demand for skilled professionals in embedded systems and IoT is booming, and the Indian Institute of Embedded Systems (IIES) is fast becoming the top embedded training institute in Bangalore. With a focus on real-world learning, hands-on projects, and guaranteed placement support, IIES offers some of the best embedded systems courses and best IoT courses for freshers, graduates, and working professionals alike. Whether you're searching for the best embedded systems course in Bangalore with placement or looking to upskill through an advanced IoT course online, IIES offers flexible programs that combine theory with practical lab work. Courses include embedded C, C++, Python, Arduino, Raspberry Pi, STM32 and more. Why IIES Stands Out Job-Oriented Embedded & IoT Courses What makes IIES one of the best institutes for embedded systems and IoT training in Bangalore is its commitment to outcomes. The institute maintains close ties with core embedded companies and tech startups that actively hire from its talent pool. Many students get placed in embedded and IoT roles within 3 to 6 months of completing the training. From beginners to advanced learners, IIES offers options like the embedded systems course for freshers with placements, automotive embedded systems course online, and advanced IoT training programs. These are designed to help you build a career—not just earn a certificate. Online and Offline Learning Options IIES understands that today's learners need flexibility and accessibility. That's why its online IoT training and embedded course programs are just as robust as the offline batches in Bangalore. With live interactive sessions, one-on-one mentorship, and assignment feedback, students can learn from anywhere and still receive the same high-quality training. Start Your Tech Career Today If you're looking for the best embedded systems training or searching for a trusted IoT training institute in Bangalore, IIES is the place to begin. New batches start soon, and seats are limited. Visit: to enroll or request a free counseling session.
Mint
2 days ago
- Science
- Mint
This small robot can fly thanks to jet engines, and may one day help in emergencies or dangerous work
The robots are here and now they can fly. At the Italian Institute of Technology, engineers have built iRonCub, a robot shaped like a person (with a baby face, for some reason) that can lift off the ground with jet engines. The robot stands as tall as a child and weighs about 70 kilograms. Its face is blank and simple. The team started with detailed computer models to design iRonCub. They used a programme called PTC Creo. The design keeps changing as they test the robot in real life. The latest version is called iRonCub MK3. It has a new titanium spine and covers that protect it from heat. There are four jet engines, two on the arms and two on the back. These engines can lift the robot and keep it in the air. The exhaust from the engines gets very hot, so the team had to make sure the robot would not get damaged. There are two main versions of iRonCub. Both are based on earlier robots called iCub. The engineers use a digital model to plan and test how the robot should move. This helps them find problems before they try new ideas on the real robot. Flying is not easy for a robot with arms and legs. The team wrote software to plan how iRonCub should move when it walks or flies. They use Python for planning and C++ for running tests. The robot is controlled by a person who wears a headset and uses special equipment. The control system keeps the robot steady and safe during flight. To know where it is, iRonCub uses sensors on its body. These sensors tell the robot its position and how it is moving. The team also built a test bench to check how much thrust each engine gives. This helps them adjust the robot for better flight. The engineers use computer simulations to study how air moves around iRonCub. They also test the robot in a wind tunnel to see how it behaves in real air. This is the first time a humanoid robot has been tested like this. iRonCub is not just an experiment. The team hopes robots like this will help in disaster zones, dangerous repairs, or inspections. The project shows how robots are changing and becoming more useful in real life, with their usefulness far surpassing their potential dangers. The research on iRonCub's flight, aerodynamics, and control was published in the journal Nature Communications Engineering and is also available as a preprint on arXiv.
Business Wire
2 days ago
- Business
- Business Wire
Europe Turns to Snowflake Partners for Data Modernization
LONDON--(BUSINESS WIRE)--Enterprises in Europe are rapidly adopting the Snowflake cloud data management platform to support real-time decision-making, accelerate AI adoption and comply with stringent regulations, according to a new research report published today by Information Services Group (ISG) (Nasdaq: III), a global AI-centered technology research and advisory firm. European enterprises need to overcome the bottlenecks of traditional on-premises data warehouses. Cloud data platforms such as Snowflake provide high performance and efficient support for concurrent users and AI workloads. The 2025 ISG Provider Lens™ Snowflake Ecosystem Partners report for Europe finds that traditional data platforms are proving inefficient as data volumes surge and enterprises embrace advanced analytics, AI and secure collaboration. As a result, companies in Europe are investing in cloud migration and infrastructure modernization. This change includes the adoption of cloud data platforms that consolidate diverse data types and eliminate silos for improved access and sharing. 'European enterprises need to overcome the scalability and performance bottlenecks of traditional on-premises data warehouses,' said Steve Hall, partner and president, ISG EMEA. 'Cloud data platforms such as Snowflake allow enterprises to scale compute and storage independently, ensuring high performance and efficient support for concurrent users and AI workloads.' To support large-scale analytics, machine learning (ML) and AI initiatives, European companies are seeking platforms that easily integrate with data science tools, support programming languages such as Python and R and enable in-database ML workflows. Many rely on Snowflake to meet these needs through its tools, accelerators and built-in connectivity with third-party ML platforms. It helps streamline data preparation, model development and deployment so organizations can securely and efficiently implement advanced AI and generative AI (GenAI) solutions, ISG says. Enterprises in Europe are also focused on transforming data into a strategic asset by sharing it securely across organizations, the report says. Increasingly, they are turning to the Snowflake Marketplace for data monetization projects. As the Snowflake ecosystem matures, service providers are playing a crucial role in helping enterprises unlock the platform's potential, design secure data-sharing architectures and establish data marketplaces. The report identifies a heightened focus on data governance, compliance and security within the Snowflake ecosystem. As European regulations such as GDPR continue to evolve, enterprises are prioritizing robust data governance frameworks, role-based access controls and continuous monitoring to safeguard sensitive information. IT service providers are helping clients implement these controls, maintain audit-ready environments and achieve regulatory compliance. 'Enterprises migrating to cloud or multicloud environments encounter challenges with data transfer, workload reconfiguration and regulatory compliance,' said Hemangi Patel, senior manager and principal analyst, ISG Provider Lens Research, and lead author of the report. 'Snowflake and its ecosystem partners simplify this transition by allowing companies to implement a fully managed, cloud-agnostic architecture.' The report also explores other trends in the European Snowflake ecosystem, including the growing importance of partnerships and rising demand for services supporting continuous learning. For more insights into challenges relevant to the Snowflake ecosystem faced by European enterprises, along with ISG's advice for addressing them, see the ISG Provider Lens™ Focal Points briefing here. The 2025 ISG Provider Lens™ Snowflake Ecosystem Partners report for Europe evaluates the capabilities of 27 providers across three quadrants: Snowflake Consulting and Advisory Services, Snowflake Implementation Services and Snowflake Managed and Support Services. The report names Accenture, Capgemini, Cognizant, Deloitte, DXC Technology, Infosys, LTIMindtree and TCS as Leaders in all three quadrants. In addition, Mphasis is named as a Rising Star — companies with a 'promising portfolio' and 'high future potential' by ISG's definition — in all three quadrants. The 2025 ISG Provider Lens™ Snowflake Ecosystem Partners report for Europe is available to subscribers or for one-time purchase on this webpage. About ISG Provider Lens™ Research The ISG Provider Lens™ Quadrant research series is the only service provider evaluation of its kind to combine empirical, data-driven research and market analysis with the real-world experience and observations of ISG's global advisory team. Enterprises will find a wealth of detailed data and market analysis to help guide their selection of appropriate sourcing partners, while ISG advisors use the reports to validate their own market knowledge and make recommendations to ISG's enterprise clients. The research currently covers providers offering their services globally, across Europe, as well as in the U.S., Canada, Mexico, Brazil, the U.K., France, Benelux, Germany, Switzerland, the Nordics, Australia and Singapore/Malaysia, with additional markets to be added in the future. For more information about ISG Provider Lens research, please visit this webpage. About ISG ISG (Nasdaq: III) is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world's top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data, in-depth knowledge of provider ecosystems, and the expertise of its 1,600 professionals worldwide working together to help clients maximize the value of their technology investments.
Fast Company
3 days ago
- Fast Company
I've become an AI vibecoding convert
A few weeks ago, I finally paid for ChatGPT Plus. It started with a simple goal: I wanted to create a personal archive of my published articles, but wasn't sure how to begin. That led to a long back-and-forth with ChatGPT, where we built a Python script to scrape my author pages, download the content, and format everything cleanly. By the time I hit the free usage limit, I was too invested to pause or switch to another chatbot. So I upgraded. In hindsight, the money ($20 per month) was well spent. For one, it worked: I now have a folder on my computer containing more than a decade's worth of articles. More importantly, this was the moment that AI tools clicked for me. I've had little success using them to write, and often recoil at the images they churn out. When I ask ChatGPT and Google Gemini for factual information, they're liable to get the details wrong on all but the most widely understood topics. But in this case, ChatGPT saved me days of tedious work—and opened my eyes to what else might now be possible. (The idea of creating code without knowing how to code has even been coined 'vibecoding' by Andrej Karpathy.) If I could use AI to build personal Python scripts, what other plugins or extensions could I try next? Web extensions, plug-ins, and more Unlike my colleague Harry McCracken, I'm not using AI to dream up entirely new apps. I already have too many apps from actual professionals on my phone and computer, and I don't trust AI (or myself) enough to compete with them. What I've really gotten into, though, is using AI to extend and improve the software I use already. For instance, I take notes and draft stories in Obsidian, an app that's endlessly extensible via user-created plug-ins. I've always dreamed of a quick note plug-in for Obsidian that matches the simplicity of Google Keep, but have yet to find anything that works. After a few hours of vibecoding, I finally built the plug-in myself. Now, through Obsidian's right sidebar, I can view all the notes from any folder in a card-based layout and edit them directly from the sidebar. The plug-in also lets me pin notes to the top, create new notes with a single click, send notes to an archive folder, and search with real-time results. It even works in Obsidian's mobile app, with the quick-notes view just a swipe away. I've also been tweaking some existing plug-ins for Flow Launcher, a free Windows app for executing quick actions from a command bar. I took a plug-in for window management and added some new sizing options, and I modified a browser history search plug-in to make it work with my current browser (Floorp). AI tools are also useful for creating browser bookmarklets, which are special kinds of bookmarks for doing things like decluttering web pages and speeding up videos. I already wrote an entire article about that, but now I've created an additional bookmarklet for downloading YouTube videos. This works by connecting to a local Python server that silently processes video links and sends them to my Downloads folder. In all cases, the process was the same: I would tell ChatGPT exactly what I was trying to make, and asked for clear, step-by-step instructions on how to make it. I'd follow the instructions, compile the code, and go back to ChatGPT for fixes or refinements. Some assembly required I don't want to oversell vibecoding as an effortless activity. Each of the above projects took hours to build, as I inevitably fall down a rabbit hole of tweaking, clarifying, and troubleshooting. That's partly because AI can be as unreliable in coding as it is in other endeavors. ChatGPT has a habit of confidently declaring that it's produced working code, only for errors to appear when compiling or running it. I've spent hours feeding it error messages, trying to get it to recognize basic syntax issues or missing functions. On several occasions, I've had to abandon a chat entirely and start a new one after the code modifications veered too far off track. Even when everything is working properly, it's easy to fall prey to scope creep. You might think it's simple to add a new feature or tweak the design, but those changes can easily turn into additional hours of refining and fixing. (In fairness, this happens in actual software development, too.) And while you can accomplish a lot without formal programming knowledge, you'll still need a solid grasp of how file systems work and some basic sense of what code should look like. ChatGPT might ask you to replace one snippet with another, or mistakenly claim it's providing full code when large portions are missing. Being able to spot when AI is about to screw up can go a long way. Take some control back One last disclaimer: I'm not nearly confident enough in what I've created to share it with the world, as I'm sure other folks would run into bugs or ask for features that I'm thoroughly unqualified to address. I also wouldn't suggest vibecoding anything that handles sensitive data or important personal information. But for the things vibecoding is good at—small, personal utilities that no one else would want to make—it's immensely satisfying and even empowering. As Techdirt 's Mike Masnick recently pointed out, lowering the barriers to software development is a great way to push back against ' enshittification ' by major tech companies, whose products inevitably get weighed down by the need to scale and extract more money from captive users. To that point, you don't even need AI anymore once the vibe coding is done. Having built what I need for the foreseeable future, I cancelled my ChatGPT Plus subscription after a single month's payment. The extended deadline for Fast Company's Next Big Things in Tech Awards is this Friday, June 27, at 11:59 p.m. PT. Apply today.
