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Unite
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Real Identities Can Be Recovered From Synthetic Datasets
- Studies suggest that synthetic AI-generated datasets containing ‘non-real’ examples, such as images of fake people, can generate personalised data from real sources. This highlights privacy concerns and the potential for the use of copyrighted data despite being derived from AI-generated datasets. The risk, reflected in a new Swiss research paper, lies in the possibility that these synthetic systems could potentially lead to facing lawsuits when finding out that the data used was, in fact, unauthorised, copyrighted, or IP-protected, especially for facial recognition and biometrics. As a result, businesses are training their AI to discriminate high-level concepts without replicating the actual training data to mitigate this risk.
- A recent investigation by the US Copyright Office in 2023 concluded that businesses using generative AI models on legally-questionable grounds could expose themselves to legal ramifications. Studies by Swiss researchers delve into the potential pitfalls of using synthetic datasets, in which examples of fake people, for example, can be synthesised without needing to consider whether the data is legally usable.
- While training AI systems on synthetic data can provide a cost-effective solution to training on copyrighted data, the Swiss researchers claim that the new data retains the trace of the real dataset from which it is derived. Moreover, the researchers found that synthetic datasets contain similar images to that of the original (real) dataset from which it was sourced. Therefore, synthetic generators have memorised training data points which could be used to infringe on privacy rights.
- To avoid this and generate high-level concepts, businesses are training AI systems on realistic examples of fake people, churches, or cats, for example. It can be difficult for trained AI systems to produce intricate details unless it is trained extensively on the dataset, which can lead to memorisation tendencies. However, if businesses set a relaxed learning rate or end training at the stage where the core concepts are ductile, not buried down to the specifics.
- Therefore, researchers generally apply comprehensive training schedules and high learning rates to produce granularity in the AI models. However, even slightly memorised systems can potentially misrepresent themselves as well-generalised, as outlined in a Swiss research paper titled, “Unveiling Synthetic Faces: How Synthetic Datasets Can Expose Real Identities,” which raises concerns about the generation of synthetic facial recognition datasets.
- The Swiss researchers demonstrated the ability to recognise the links between synthetic and real datasets, raising concerns regarding the application of synthetic data in biometrics and face recognition, given the risk of sensitive information leakage and paving the way for generating responsible synthetic face datasets in the future that also address privacy concerns.
- Bloomberg suggested that user-supplied images from the MidJourney generative AI system had already been incorporated into the capabilities of Adobe's Firefly – its text-to-image, and now text-to-video architecture – that is powered primarily by the Fotolia stock image dataset, which Adobe acquired in 2014, supplemented by the use of copyright-expired public domain data. As a result, businesses must train AI models to discriminate high-level concepts without replicating actual training data by using synthetic datasets.
- Though the authors of the research promise to release code for the work, there is no current repository link. The paper is called, “Unveiling Synthetic Faces: How Synthetic Datasets Can Expose Real Identities” and comes from the Idiap Research Institute, the Ecole Polytechnique Federale de Lausanne, and the Universite de Lausanne in Switzerland. It was published on November 6, 2024.
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Medium
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Robotic Programming Classes in Dubai
- Robotic programming enables students to create living devices by fusing engineering and coding.
- Dubai offers numerous educational institutions and facilities providing age-appropriate robotic programming courses.
- Students can learn robotic programming through both in-person classes and online programs.
- Robotic programming lessons in Dubai help develop knowledge, creativity, and confidence in the field of robotics.
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The Robot Report
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NVIDIA adds open AI and simulation tools for robot learning, humanoid development
- NVIDIA has announced new AI and simulation tools aimed at accelerating the development of robot humanoid, including the NVIDIA Isaac Lab robot learning framework and six new robot learning workflows for the Project GR00T initiative to accelerate humanoid development.
- Hugging Face and NVIDIA are collaborating to accelerate open-source robotics research with LeRobot, NVIDIA Isaac Lab, and NVIDIA Jetson.
- The Cosmos tokenizer is designed to minimize distortion, running up to 12 times faster than current tokenizers.
- Curating video data poses challenges, with the massive size requiring scalable pipelines and efficient orchestration for load balancing across GPUs.
- NeMo Curator streamlines data curation by reducing video processing time and enables robot developers to improve their world-model accuracy.
- Hugging Face's AI platform, which includes APIs with more than 1.5 million models, datasets, and applications now works with NVIDIA Isaac Lab on Isaac Sim, enabling training by demonstration or trial and error in realistic simulation.
- Initial steps in the collaboration have shown a physical-picking set up with LeRobot software running on NVIDIA Jetson Orin Nano, providing a compact compute platform for deployment.
- NVIDIA has added six new workflows intended to help robots perceive, move, and interact with people and their environments as part of the Project GR00T blueprints.
- NVIDIA Cosmos tokenizer provides high-quality encoding and decoding to simplify the development of world models with minimal distortion and temporal instability.
- NVIDIA NeMo Curator reduces video processing time and enables robot developers to improve their world-model accuracy by processing large-scale text, image, and video data.
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Insider
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Jeff Bezos just made his latest bet in the AI robotics space. Here are the 6 startups he's backed so far.
- Jeff Bezos has made significant investments in the AI robotics space, backing six startups focused on spatial intelligence—robots powered by AI to navigate and interact with their environment.
- This includes Physical Intelligence, which raised $400 million in November 2024, and aims to bring general-purpose AI into physical tasks.
- Other investments include Swiss-Mile, developing AI-driven wheeled robots, Figure AI for unsafe job automation, Deep Sentinel for AI-powered home security, Fathom Radiant for AI hardware, and Rethink Robotics, which creates robots for manufacturing. Bezos sees AI robotics as a solution to labor shortages and rising costs across various industries.
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Analyticsindiamag
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Bengaluru-based Robotics Startup CynLr Raises $10 Mn to Bring Automation in Manufacturing
- Bengaluru-based Robotics Startup CynLr has raised $10 million in Series A funding.
- The funding will be used to expand the workforce, supply chain, and improve hardware and software.
- CynLr aims to double its robotics lab in Bengaluru and manufacture one robot system per day.
- The company's flagship product, CyRo, is a modular robot that can handle various objects without specific training.
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Digitaltrends
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OpenAI’s robotics plans aim to ‘bring AI into the physical world’
- OpenAI has appointed Caitlin Kalinowski, former head of hardware at Oculus VR, to lead its robotics and consumer hardware team.
- Kalinowski will focus on OpenAI's robotics work and partnerships to bring AI into the physical world.
- OpenAI is rumored to be partnering with product designer Jony Ive on an upcoming AI hardware project.
- OpenAI plans to build its own AI chips and is partnering with Broadcom, AMD, and Nvidia to expand its compute infrastructure.
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Eweek
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8 Top AI Certifications: Latest Hotlist You Won’t Want To Miss
- AI certifications demonstrate a specified level of proficiency and competence in job-related skills, making you more attractive to employers.
- As AI continues to transform industries, certifications are becoming increasingly important to recruiters who seek assurance that candidates understand the fundamentals of AI and its various aspects, including machine learning, natural language processing, computer vision, robotics, and AI software.
- Here are our picks for the top 8 AI certifications in 2024 for learners of all levels: AI for Everyone, Computer Science for Artificial Intelligence, Introduction to TensorFlow for Artificial Intelligence, IBM AI Engineering Professional Certificate, Certified AI Professional, CertNexus Certified Artificial Intelligence Practitioner Professional Certificate, Advanced AI Techniques, and Artificial Intelligence Engineer (AiE) Certification.
- The cost, experience level, certifying institutions, duration, and shareable certificate of the seven leading AI certification courses have been compared in a chart to help find the one that suits you best.
- AI for Everyone by DeepLearning.AI is ideal for anyone seeking a foundational understanding of AI. Designed for learners with no prior background, this course focuses on practical applications and real-world scenarios. It has modules focusing on potential AI applications, working with an AI team, and navigating the workflow of machine learning and data science projects.
- The Computer Science for AI course offered by Harvard University provides a solid foundation in programming skills essential for AI. The program starts with CS50’s Introduction to Computer Science course, ensuring learners have a solid foundation of core programming skills in Python, followed by the concepts and algorithms of modern AI.
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning provided by Deeplearning.ai on Coursera is ideal for individuals interested in AI, ML, and DL. Its hands-on practical exercises and assignments provide valuable experience in using TensorFlow to solve real-world problems. The course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate, which helps you prepare for the Google TensorFlow Certificate exam.
- IBM AI Engineering Professional Certificate offered by IBM provides comprehensive expertise in machine learning and deep learning. This program goes beyond basic theoretical knowledge and digs deeper into practical applications, offering learners the tools and skills that employers in the AI industry look for. This professional certificate helps you gain the knowledge and skills needed to start a career in AI engineering or furthering the existing one.
- CertNexus Certified Artificial Intelligence Practitioner Professional Certificate designed for data scientists looking to enhance their skills and knowledge in the AI space. This certification stands out for its comprehensive five-course series that helps you earn an industry-validated certification from a respected organization. You can also add the projects that you complete in your work portfolio.
- ARTiBA AI Engineer (AiE) Certification offered by the Artificial Intelligence Board of America is specifically designed to demonstrate your expertise in building and deploying AI systems. It emphasizes the ARTiBA-developed AMDEX knowledge framework, which goes beyond platform-specific tools and focuses on in-depth practical skills. Gaining this certification helps you stand out in the competitive AI industry.
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The Robot Report
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Pipedream Labs deploys underground robotic delivery system in Texas drive thru
- Pipedream Labs Inc. launched its robotic food-delivery system at a leading quick-service restaurant in Texas.
- The system delivers food orders from the kitchen to the customer in under 15 seconds with the help of underground robots.
- Canon Reeves, CTO and co-founder of Pipedream, said autonomous delivery has a long way to go before it becomes a reality.
- Pipedream raised $13m in venture capital to develop a hyper-efficient delivery system using smart pipes and robots.
- Pipedream is dedicated to revolutionizing logistics by streamlining restaurant operations and reduce delivery times.
- Pipedream's system will use above-ground kiosks where customers can pick up their orders.
- The system is similar to the pneumatic tubes in banks or pharmacies with food and drink delivery being the new challenge.
- Pipedream aims to bring down the construction time to just two or three days from four and a half days of a recent deployment.
- Pipedream's focus is on developing a city-wide backbone for autonomous logistics and could complement other delivery systems.
- Pipedream claims to provide a safer and more reliable alternative to other robotic delivery methods.
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The Robot Report
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From surge to sobriety: the state of robotics investment in 2024
- Robotics startups have had difficulty securing investment in recent years, due to a general downturn in the tech industry affecting resource-intensive technologies like robotics.
- However, the investment environment has changed in 2024, with investment across all of 2024 expected to approach the all-time highs seen in 2021.
- Lower costs and higher performance of technology, including computing power, sensors, motors and batteries, combined with accelerating advances in AI, are now driving growth in the robotics sector.
- A new category has been added to robotics, humanoids, which had an investment of nearly $1bn by August 2024, with companies Apptronik, Figure and 1X commanding large funding rounds.
- Tesla and Boston Dynamics are investing heavily in-house in building their own humanoids.
- After falling off in 2022, investment in autonomous vehicles (AVs) is once again the majority investment in robotics. For example, Waymo reached 100,000 rides per week and Aurora has expanded its operations to new states.
- The software layer has been a focus of investment this year, particularly in foundational models as companies want to overcome interoperability, scalability and reliability challenges.
- Vertical Robotics has experienced steady growth, with interest in applying it to defence and agriculture industries.
- While funding in robotics has surged, the majority of capital has gone to large, mostly late-stage funding rounds. Earlier rounds are actually down year-on-year.
- There's a lack of successful robotics exits with much of the value remaining locked up in private unicorns, and a lack of M&A or public offerings continues to be an industry headwind.
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The Robot Report
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RBR50 Spotlight: Ukrainian tractor company develops demining robot
- Ukraine-based Gardarika Tres LLC develops a demining robot.
- The demining system includes a drone, autonomous tractor, and demining attachment.
- The tractor is equipped with additional armor plates for mine protection.
- The system aims to clear minefields in Ukrainian agricultural land.
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Unite
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Quantum Computing: The Future of Data-Driven Decision Making
- Quantum computing has the potential to enhance decision-making processes by accurately processing large volumes of data.
- Data is the lifeblood of businesses, driving long-term strategy and competitiveness, and companies generate more data than ever before from all sources.
- Conventional systems struggle with accuracy and energy efficiency, which are crucial in today’s world where operational costs and environmental impact are key concerns for businesses.
- Quantum computing introduces qubits, which can exist in multiple states at the same time and perform more complex calculations at record speeds when compared to classical computing.
- Quantum computing technology helps organizations make more informed and strategic decisions and stay ahead of their competitors, especially in fast-moving industries, where speed is imperative.
- Neutral atom quantum computing stands out among different modalities due to its unique method of using individual neutral atoms, offering high coherence, low noise, and being less susceptible to external electromagnetic fields.
- With quantum computing, the speed and efficiency at which computers can operate has the potential to drive progress forward and improve outcomes across various sectors and industries, such as finance and healthcare.
- Quantum computing marks a significant advancement in addressing the constraints faced by conventional computing systems, allowing businesses to harness their data's full potential.
- By leveraging the capabilities of quantum computing, every organization can unlock new opportunities for growth and innovation.
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Unite
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Heico Sandee, Founder and CEO of Smart Robotics – Interview Series
- Heico Sandee is a co-founder and CEO of Smart Robotics, a company that offers technology and services designed to automate pick-and-place stations in fulfillment centers. Smart Robotics provides user-friendly, reliable, and adaptable pick-and-place systems capable of handling a wide variety of items.
- Smart Robotics was founded in 2015 by Heico Sandee and Mark Menting. The company is focused on offering more flexible and innovative pick and place automation in response to the ever-increasing and varying consumer demand.
- Smart Robotics has evolved over the past nine years and has developed a strong partner network in Europe and beyond. Smart Robotics' pick and place robots are utilized by various industries in Europe, particularly in the Benelux and Dach regions. The solutions are most impactful in the food, retail, pharma, and parcel logistics industries.
- Smart Robotics designs robots to work alongside humans, improving speed and accuracy of palletizing tasks without safety fences because these robots can continue operation even with an operator nearby.
- Smart Robotics has provided tailored robotic solutions for precise, repetitive tasks like order picking, and packing. Smart Robotics' advanced vision and task planning capabilities ensure accurate handling of sensitive pharmaceutical items, enhancing efficiency, minimizing human error, and improving overall operational safety.
- AI plays a fundamental role in Smart Robotics' robotic systems by enabling robots to autonomously navigate complex logistics tasks. Continuous learning allows the robots to improve with each task, adapting to new items, environments, and challenges without needing manual intervention.
- The Technology Trinity (motion, vision, and decision-making) is a core innovation for Smart Robotics. Vision is powered by 3D camera sensors and deep learning, enabling precise detection of items in their surroundings.
- Smart Robotics software integrates seamlessly with a wide range of robotic systems, independent of the hardware in use, offering flexibility to clients across different industries.
- Smart Robotics envisions the future of warehouse automation and robotics where a team of robots, guided by advanced software and AI, can efficiently handle products and packages alongside humans, making their tasks easier and more effective and safer.
- The company will play a vital role in the anticipated 50% or greater increase in robotics use in warehouses worldwide over the next five years.
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Unite
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Huawei’s Ascend 910C: A Bold Challenge to NVIDIA in the AI Chip Market
- Huawei's Ascend 910C is a significant challenge to NVIDIA’s dominance in AI chip market, particularly in China, as the Ascend 910C's competitive performance, energy efficiency, and integration within Huawei's ecosystem make it a strong contender for enterprises looking to scale their AI infrastructure.
- Huawei's Ascend 910C promises competitive performance, energy efficiency, and strategic integration within Huawei’s ecosystem, potentially reshaping the dynamics of the AI chip market.
- The Ascend series began with the Ascend 310 designed for edge computing, and the Ascend 910 aimed at high-performance data centers.
- The Ascend 910 was recognized as the world's most powerful AI processor, delivering 256 teraflops (TFLOPS) of FP16 performance, while the Ascend 910C promises up to 320 TFLOPS of FP16 performance and 64 TFLOPS of INT8 performance.
- NVIDIA's A100 and H100 GPUs, built on the Ampere and Hopper architectures, respectivel, with A100 delivering up to 312 TFLOPS of FP16 performance and H100 offers even more robust capabilities.
- Reports indicate that Huawei has started distributing prototypes of the Ascend 910C to major Chinese companies, including ByteDance, Baidu, and China Mobile.
- The success of the Ascend 910C will rely heavily on Huawei's ability to develop a robust software ecosystem and strengthen its strategic partnerships to solidify its position in the evolving AI chip industry.
- The AI chip industry will likely keep evolving, with technologies like quantum computing and edge AI reshaping the domain.
- Huawei aims to strengthen its foundations in the AI chip market by continuing to invest in research and forming strategic partnerships.
- Geopolitical factors have significantly influenced Huawei's strategy. With US restrictions limiting its access to advanced semiconductor components, Huawei has increased its investments in R&D and collaborations with domestic chip manufacturers.
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The Robot Report
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Standard Bots acquires READY Robotics’ IP to advance AI for robot training
- Standard Bots has acquired all the IP of READY Robotics, comprised of ForgeOS robot-agnostic operating system’s software, patents, and trademarks.
- Standard Bots plans to market READY's API with its own training software and to bring its UI and AI platform to NVIDIA Omniverse and other robot vendors.
- The acquisition will enable Standard Bots to make its AI control software usable with multiple robot brands.
- READY had raised $40m in eight years, but reportedly had difficulty persuading robot manufacturers to work with ForgeOS, and shut down in August. Standard Bots, which is focused on using AI to train robots, acquired only the IP of READY Robotics.
- Standard Bots has already developed applications for its robot, the RO1 arm, which has a built-in 3D camera.
- The company is developing AI-capable robots from the ground up with a safety layer.
- The technology aims to prevent an AI model from driving robot arms into a collision by building new robots designed from the ground up to run AI models with safety built-in.
- Research labs working on foundation models are already using Standard Bots' integrated systems. The company also provides handheld devices for imitation learning, enabling robots to generalize behavior and correct motion in real time.
- Standard Bots believes its technology can help avoid much of the time and expense currently spent on developing industrial robot applications. Users can collect training data, fine-tune, and train on top of a foundation model, and deploy to any major robot brand.
- Standard Bots has already developed specific solutions for welding, machine-tending, and palletizing applications. The company is committed to the task of democratising technology by making robots more accessible and easier to train.
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Insider
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OpenAI hires Meta's former AR glasses lead to head its robotics team
- OpenAI has hired Meta's former hardware lead, Caitlin Kalinowski, to head its robotics team.
- Kalinowski previously led Meta's AR glasses hardware team and oversaw the creation of Orion, Meta's prototype AR glasses.
- OpenAI is focusing on bringing AI into the physical world and unlocking its benefits for humanity.
- This hire indicates OpenAI's reinvestment in its robotics efforts after shutting down the team in 2020.
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