Aibuild’s Post

Good R&D engineers have a different mindset. It's not about being the smartest engineer. It's about developing a bias towards action and making quick decisions. It's about building and testing parallel options, to learn quickly. The successful hardware design engineers learn this early in their career. There's no magic. Build, test, learn, iterate #sketchyengineering #3dprinting, #rapidprototyping

The key to success in hardware design lies in the ability to adapt and iterate. The best engineers know that there’s no magic—just a continuous cycle of building, testing, learning, and evolving.

Join us Work with cutting-edge technologies. Utilize your problem-solving ability in day-to-day software development. DM for a referral with the serial number. #ProblemSolving #Algorithm #DS #JOBS #Semiconductor #KLA #development #simulation #opticalPhysics #Connection

Some software engineers sometimes forget they're engineers too. Understanding how components work and fit together, libraries and even the underlying infrastructure of technologies will help a lot in delivering the optimum software or processes. Simply trying to ensure things work is not all that there is, just like forcing two parts together for a machine, despite obvious restrictions isn't always the way to go (force has its place though). Now I was thinking of some product designers (fortunately I haven't met yet) before typing this post. As regards Product Design, your counterpart in the hardware/physical machinery space is Engineering Design. There's an engineering/development part to what you do, you'll be a better Designer if you have some software engineering knowledge. What you do isn't just art btw I think this AI generated image looks nice. #software #productdesign #overbrim #engineering

My Wishlist for EDA Tool Debugging Improvements 🛠️✨ As someone who has worked across the VLSI spectrum—from architecture, design, and simulation to verification, formal methods, synthesis, STA, and physical design—I’ve noticed a significant gap in one critical area: debugging 🧐. While EDA tools have made strides in capacity and algorithmic improvements, debugging hasn’t kept up with user expectations. 💡 Did you know? Studies show that most of the time of an engineer’s time is spent debugging. Think about the cost in terms of productivity and resources! Debugging inefficiencies don’t just waste time—they drain budgets 💸. Contrast this with modern mobile apps: when you click a button, complex calculations happen seamlessly in the background, delivering instant results. EDA tools? Not quite there yet. 🚀 My Wishlist for Next-Level EDA Debugging 1️⃣ Radical Improvements in Debugging Efficiency Incremental changes won’t cut it anymore. We need a 10X leap in debugging capabilities across the board. Time to disrupt the status quo! ⚡ 2️⃣ Seamless Collaboration Across Tools & Teams 🤝 Debugging should work across tools and teams: Start in an STA tool and seamlessly continue in a PD tool without losing context. Allow one engineer to pick up where another left off, enabling collaborative workflows. 3️⃣ AI-Driven Triage & Root Cause Analysis 🤖 Let AI do the heavy lifting! Automatically triage regressions and link them to root causes. Use intelligent agents to save engineers from chasing issues manually, allowing more focus on innovation. Let’s rethink EDA debugging for the future 🌟. It’s time for tools to enable us, not hold us back. What’s on your debugging wishlist? Let’s connect and discuss! #EDA #VLSI #DebuggingRevolution #Innovation #TechWishList #Semiconductor #AI #ProductivityBoost #Engineering

🔧 Essential Tools & Software for Biomedical Engineers 🧬 Hey everyone! I've put together a handy list of tools and software that every biomedical engineer should know about. Whether you're just starting out or looking to expand your toolkit, this list has something for you. 📊 Categories Covered: 3D CAD Design Programming Languages Computing Software Simulation Tools Image Processing Software Analysis Tools 🔗Check it out and let me know what you think! #BiomedicalEngineering #ToolsAndSoftware #Engineering #3D #AutoCAD #SolidWorks #Python #C #Arduino #R #MATLAB #Simulink #Simulation #ANSYS #ComsolMultiphysics #ImageJ #Fiji #CellProfiler #ImageProcessing #Analysis

Modelithics, Inc. Releases New Library with 2110 Additional Components for Cadence AWR Design Environment Read more: https://ow.ly/Fi1750Usrfs #software #modelithics #cadence #design #engineers

𝐋𝐋𝐌-𝐀𝐢𝐝𝐞𝐝 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐇𝐚𝐫𝐝𝐰𝐚𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 The paper discusses how large language models (LLMs) can be integrated into the EDA workflow to simplify and automate various tasks, including: 𝐇𝐃𝐋 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧: LLMs can be used to automatically generate hardware description language (HDL) code from design specifications. 𝐂𝐨𝐝𝐞 𝐝𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠: LLMs can assist engineers in identifying and fixing syntax and functional errors in HDL code. 𝐃𝐞𝐬𝐢𝐠𝐧 𝐯𝐞𝐫𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧: LLMs can generate test scenarios and testbenches to improve testing and verification of hardware designs. 𝐏𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: LLMs can help automate the process of transitioning from RTL to GDSII layout. It also presents two case studies demonstrating the use of LLMs for C/C++ code repair in High-Level Synthesis (HLS) and automatic testbench generation for HDL designs. The research is significant because: 𝐈𝐧𝐜𝐫𝐞𝐚𝐬𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 𝐨𝐟 𝐡𝐚𝐫𝐝𝐰𝐚𝐫𝐞 𝐝𝐞𝐬𝐢𝐠𝐧: Modern chip design has become increasingly complex, requiring more effort from engineers in tasks like circuit design, verification, and physical implementation. Automating these workflows can greatly improve efficiency. 𝐍𝐞𝐞𝐝 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐄𝐃𝐀 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬: There is a growing need for more cost-effective and automated EDA tools to accelerate hardware development and reduce errors. 𝐏𝐫𝐨𝐦𝐢𝐬𝐢𝐧𝐠 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐨𝐟 𝐋𝐋𝐌𝐬: LLMs have shown remarkable advancements in areas like natural language understanding and generation, making them a promising technology to integrate into EDA. 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 𝐭𝐨 𝐬𝐢𝐦𝐩𝐥𝐢𝐟𝐲 𝐚𝐧𝐝 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐄𝐃𝐀: By leveraging LLMs, the paper explores how the entire EDA workflow, from specification to physical implementation, could be simplified and automated, reducing human effort. 🙏 #research #llms #genai #product #automation