News

Intrinsic Flowstate aims to change robotic software development

Source: The Robot Report, May 15, 2023 [1]
Intrinsic unveiled a new robotic software development solution today with the goal of making it easier to develop applications for robots. The Intrinsic Flowstate software adds a layer of abstraction to traditional robotic software tools with the goal of reducing the development skillset required while making it easier than ever before to program a robot in simulation.

Chip manufacturing ‘Ideal application’ for AI, nvidia ceo says

Source: NVIDIA Blog, May 16, 2023 [2]
NVIDIA CEO Jensen Huang outlines role of accelerated computing and AI in address to semiconductor industry leaders at ITF World 2023.

Chip war without soldiers

Source: Semiwiki, May 16, 2023 [3]
This article aims to inspire electrical and electronics engineers to lead the semiconductor industry and VLSI Design companies to upskill and support their chip design workforce for their long-term career development.

Can Intel bounce back?

Source: Financial Times, May 10, 2023 [4]
Intel has a plan to jump back to the top of the semiconductor chip industry

Soft robotics and new materials will have the biggest impact on industry, says Protolabs report

Source: Robotics & Automation News, May 12, 2023 [5]
A new Protolabs report reveals that almost one third (32 percent) of robotics industry experts believe that soft robotics and new materials will have the biggest impact on how robotics manufacturing will develop in the next five years.

Silicon catalyst and arm announce $150,000 silicon startup contest!

Source: Semiwiki, May 16, 2023 [6]
The contest offers an opportunity for silicon startups to win valuable commercial, technical and marketing support from Arm and Silicon Catalyst. The winner will receive Arm credit worth $150,000, which could cover IP fees for a complete embedded system, or significantly contribute to the cost of a higher performance application.

Experts weigh impact of Intel-Arm collaboration

Source: EETimes, May 15, 2023 [7]
Intel Foundry Services and Arm will optimize Arm's IP for Intel's 18A process technology to optimize performance, power, and costs. This collaboration will lead to the development of an Arm-based mobile SoC and silicon technology demonstration platform.

On device AI – double-edged sword

Source: SemiAnalysis , May 13, 2023 [8]
The AI industry is chasing ever-larger language models, which are costly and difficult to deploy. OpenAI's GPT-4 and Google's full-size PaLM models require 8 GPUs, 64 TPUs, 16 CPUs, and 128 GPUs to run. However, there is a thriving ecosystem of model development geared towards on-device inference. This discussion will focus on the gating factors for inference performance, the fundamental limits to model sizes, and how hardware development will establish the boundaries of development.

AMD versal AI edge soc FPGA system-on-module targets ADAS, robotics, medical imaging, and other AI applications

Source: CNX Software - Embedded Systems News, May 12, 2023 [9]
iWave Systems iW-Rainbow-G57M is a SoM designed to deliver AI acceleration at low power for demanding applications.

What is a semiconductor?

Source: McKinsey & Company, May 15, 2023 [10]
Semiconductors are the unsung heroes of the technology world: parts manufactured from pure elements that work behind the scenes to power and connect everything from smartphones to cars.

Papers

Autonomous systems: Indoor drone navigation

Source: arXiv, April 18, 2023 [11]
Drones are a promising technology for autonomous data collection and indoor sensing, offering flexibility, cost savings, and reduced risk. The goal is to create a simulated drone that can move autonomously in an indoor (gps-less) environment.

Transformer-based models and hardware acceleration analysis in autonomous driving: A survey

Source: arXiv, April 21, 2023 [12]
Transformer architectures have been successful in autonomous driving applications, but their dedicated hardware acceleration on portable computational platforms is essential for practical deployment. This paper provides an overview, benchmark, and analysis of Transformer-based models tailored for autonomous driving tasks.

Previous Hardware Acceleration in Robotics Newsletters

  • Hardware Acceleration in Robotics #59 - India’s robot installations hit an all-time high, Nvidia business model, India surging up the industrial robot ranks and more
  • Hardware Acceleration in Robotics #58 - Acceleration Robotics hosts ROS developers meet-up in Delhi, India, Global chip sales and wafer shipments drop again in Q1 and more
  • Hardware Acceleration in Robotics #57 - Design IP Sales Grew 20.2% in 2022 after 19.4% in 2021 and 16.7% in 2020, Demand for robot vision system is anticipated to reach $7 billion by 2033 and more
  • Hardware Acceleration in Robotics #56 - EU legislators strike deal on €43B chips plan, Global semiconductor manufacturing equipment sales reach all-time record $108 billion and more
  • Hardware Acceleration in Robotics #55 - India is the world’s next tech manufacturing hub, EU chips act likely to get green light on April 18 -sources and more
  • Hardware Acceleration in Robotics #54 - The age of acceleration engines, Keys to using ROS 2 & other frameworks for medical robots, Autonomous mobile robots market expected to expand at 22 percent a year and more
  • Hardware Acceleration in Robotics #53 - Robotekin, the Basque robotics and automation association, Automotive industry sets record by employing 1M robots and more
  • Hardware Acceleration in Robotics #52 - Nvidia works with TSMC, ASML and Synopsis on software to speed up chipmaking, Keys to developing autonomous vehicle software and more
  • Hardware Acceleration in Robotics #51 - PRESS RELEASE: Peer Robotics partners with Acceleration Robotics to bring hardware acceleration to their collaborative AMR, ROS 2 Hardware Acceleration Working Group #16 and more
  • Hardware Acceleration in Robotics #50 - How the EU chips act could build "Innovation capacity" in Europe, How Efinix is conquering the hurdle of hardware acceleration for devices at the edge and more

Past ROS 2 Hardware Acceleration Working Group meetings

  1. Oitzman, M. (2023, May 15). Intrinsic Flowstate aims to change robotic software development. The Robot Report. https://www.therobotreport.com/intrinsic-flowstate-aims-to-change-robotic-software-development/ ↩︎

  2. ↩︎

  3. PR, S. (2023, May 12). Chip war without soldiers. Semiwiki. Retrieved May 16, 2023, from https://semiwiki.com/semiconductor-services/maven-silicon/328918-chip-war-without-soldiers/ ↩︎

  4. Tindera, M., & Waters, R. (2023, May 10). Can Intel bounce back? Financial Times. https://www.ft.com/content/23e082c1-a911-48fd-83ec-74829b7024b3 ↩︎

  5. Allison, M. (2023, May 12). Soft robotics and new materials will have the biggest impact on industry, says Protolabs report. Robotics & Automation News. https://roboticsandautomationnews.com/2023/05/12/soft-robotics-and-new-materials-will-have-the-biggest-impact-on-industry-says-protolabs-report/68268/ ↩︎

  6. Nenni, D. (2023, May 10). Silicon catalyst and arm announce $150,000 silicon startup contest! Semiwiki. https://semiwiki.com/semiconductor-services/silicon-catalyst/328649-silicon-catalyst-and-arm-announce-150000-silicon-startup-contest/ ↩︎

  7. Shilov, A. (2023, May 15). Experts weigh impact of Intel-Arm collaboration. EETimes. https://www.eetimes.com/experts-weigh-impact-of-intel-arm-collaboration/ ↩︎

  8. Patel, D. (2023, May 13). On device AI – double-edged sword. SemiAnalysis | Dylan Patel | Substack. https://www.semianalysis.com/p/on-device-ai-double-edged-sword?utm_source=substack&utm_medium=email ↩︎

  9. (CNXSoft), J. A. (2023, May 12). AMD versal AI edge soc FPGA system-on-module targets ADAS, robotics, medical imaging, and other AI applications. CNX Software - Embedded Systems News. https://www.cnx-software.com/2023/05/12/amd-versal-ai-edge-soc-fpga-system-on-module-targets-adas-robotics-medical-imaging-and-other-ai-applications/ ↩︎

  10. What is a semiconductor? (2023, May 15). McKinsey & Company. https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-a-semiconductor ↩︎

  11. Iyer, A., Narayan, S., Naren, M., & Rajapogal, M. (2023, April 18). Autonomous systems: indoor drone navigation. arXiv. https://arxiv.org/ftp/arxiv/papers/2304/2304.08893.pdf ↩︎

  12. Zhong, J., Liu, Z., & Chen, X. (2023, April 21). Transformer-based models and hardware acceleration analysis in autonomous driving: A survey. arXiv. https://arxiv.org/abs/2304.10891 ↩︎