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Unite
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William Falcon, Founder and CEO of Lightning AI – Interview Series
- Lightning AI is the creator of PyTorch Lightning, a framework designed for training and fine-tuning AI models, as well as Lightning AI Studio.
- PyTorch Lightning quickly gained traction in both academia and industry, which led me to found Lightning AI (initially Grid.ai) in 2019.
- Our goal was to create an “operating system for artificial intelligence” that could unify the fragmented AI development ecosystem.
- Our evolution reflects a vision to simplify and streamline the entire AI development process, reducing the time and resources required for machine learning initiatives and honoring the growing community of developers who had come to rely on our tools.
- Lightning AI aims to be the catalyst for this change, enabling individuals and organizations of all sizes to bring their AI ideas to life quickly and efficiently.
- We've designed the framework to eliminate boilerplate code and standardize best practices, which significantly speeds up development and reduces errors.
- At Lightning AI, we're preparing for these shifts by building a flexible, scalable platform that can adapt to emerging technologies.
- Entrepreneurship taught me to identify market needs and translate innovative ideas into practical solutions.
- At Lightning AI, we are deeply committed to using AI for societal good, and we believe that open source is the key to achieving this.
- Ultimately, we see Lightning AI as a catalyst for positive change, empowering a global community to harness AI for the greater good.
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Unite
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Fighting AI with AI in the Modern Threat Landscape
- AI has dramatically changed the cybersecurity industry.
- Adversaries are mostly using AI to increase the scale and complexity of their attacks.
- If small tweaks to malware code can effectively camouflage it from detection tools, attackers can get far more mileage out of an individual malware program before they need to move on to something new.
- With attacks happening at an ever-increasing scale, security teams are often stretched thin.
- AI solutions are playing an important role in alleviating that challenge by providing automated detection and response capabilities.
- Security teams often find the most success when they use AI to amplify their existing capabilities.
- Far from having a negative impact on human operators, AI solutions are enabling humans to do their jobs better and more efficiently.
- AI solutions are handling much of the perceived “busywork” associated with security positions, allowing humans to focus on more interesting and important tasks.
- As attackers use AI to increase the speed, scale and complexity of their attacks, security teams will need to fight fire with fire.
- The AI arms race is only getting started—but the fact that security professionals are already using AI to stay one step ahead of attackers is a very good sign.
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Medium
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Part 4 — A Mathematical Framework for Fluid Intelligence
- AGI is a process that demands abstracting knowledge from previous actions, leveraging Bayesian priors, and extrapolating insights to unknown scenarios.
- Fluid intelligence is the capacity to think logically and solve novel problems independently of acquired knowledge; it involves abstract reasoning, pattern recognition, and adaptability in unfamiliar situations.
- The challenge in constructing AGI lies in its ability to learn a new governing function in a way that is conditioned on previously learned functions without exhaustive new data.
- The mathematical framework for learning f_An+1(x,y,z,t,s) instantaneously is by framing the learning process as an adaptive Bayesian inference problem, where each f_Ak acts as a probabilistic prior, enabling the system to infer fAn+1 with minimal new observations.
- The optimization problem is to minimize the dependency on new observations for the (n+1)-th action, while ensuring that the model can accurately approximate fAn+1 within a confidence interval.
- Each new observation updates the posterior distribution for fAn+1, conditioning it on both the spatial-temporal domain and the high-dimensional state vector.
- The AGI model achieves a balance between generalization and specificity by iteratively integrating prior knowledge across varied actions, continuously refining its posterior beliefs, and generalizing seamlessly to new, unseen actions.
- Thus, this approach equips AGI models with a fluid ability to map complex dynamics across high-dimensional, multi-modal spaces instantaneously and with minimal data by capturing the essence of human-like adaptability in an algorithmic structure.
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Mit
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A faster, better way to train general-purpose robots
- MIT researchers developed a versatile technique that combines a huge amount of heterogeneous data from many of sources into one system that can teach any robot a wide range of tasks.
- Their method involves aligning data from varied domains, like simulations and real robots, and multiple modalities, including vision sensors and robotic arm position encoders, into a shared “language” that a generative AI model can process.
- This approach can be used to train a robot to perform a variety of tasks without the need to start training it from scratch each time.
- This method could be faster and less expensive than traditional techniques.
- Their architecture called Heterogeneous Pretrained Transformers (HPT) that unifies data from these varied modalities and domains.
- The researchers align data from vision and proprioception into the same type of input, called a token, which the transformer can process.
- The larger the transformer becomes, the better it will perform.
- When they tested HPT, it improved robot performance by more than 20 percent on simulation and real-world tasks, compared with training from scratch each time.
- This approach enables robot learning methods to significantly scale up the size of datasets that they can train on.
- The researchers are working towards creating a universal robot brain that can be downloaded and used for robots without any training.
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Medium
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The idea of robots turning against humanity often sounds like the plot of a science fiction movie.
- Robots lack an understanding of moral consequences and can cause unintended destruction.
- As automation increases, ethical questions arise regarding unintended consequences of automated actions.
- Integrating artificial intelligence with robots gives them autonomy to make decisions without human input.
- To prevent harm, safety measures, human oversight, and ethical programming are crucial in the development of autonomous systems.
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Dev
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Setting Up an Ubuntu Dev Environment with Multipass and VS Code Remote-SSH
- Ubuntu is often the go-to operating system for many open-source tools and libraries.
- Setting up a dedicated Ubuntu development environment that doesn't disrupt your daily workflow can be easily achieved with Multipass, a tool for running lightweight Ubuntu VMs on your computer.
- You will need Multipass tool, Visual Studio Code (VS Code) and VS Code Remote - SSH Extension. Also, you will need a basic understanding of the command line to install tools and manage your VM.
- Step 1 is to install Multipass and launch your Ubuntu VM. Once launched, connect to it using the 'multipass shell ubuntu-dev' command. Verify that your instance is runnning using the 'multipass list' command
- Step 2 is to set up VS Code with Remote - SSH and connect it to your VM. You can mount a local folder by using command 'multipass mount /some/local/path ubuntu-dev:/some/remote/path'
- Step 3 is to set up your development tools in Ubuntu. Install essentials such as Git and build-essential. For embedded development, robotics, or cybersecurity, install domain-specific tools.
- Step 4 is to set up for embedded development, robotics, and cybersecurity. Installing ROS (Robot Operating System) on Ubuntu is straightforward and fully supported.
- Step 5 is maintenance and snapshot management. Multipass makes it easy to take snapshots, which allow you to create backups of your development environment.
- By isolating your development environment in Ubuntu, you gain access to the rich Linux ecosystem, which includes tools specifically tailored to robotics, embedded systems, and cybersecurity, while maintaining your main OS for everyday tasks.
- This setup offers a powerful and versatile development workflow that is ideal for building an IoT solution, exploring autonomous vehicle software or working on network security.
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The Robot Report
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FarmDroid obtains over $11M to deploy its modular robot globally
- FarmDroid, a company developing a solar-powered, autonomous robot for agriculture, has secured a $11.37 million investment.
- The investment will help FarmDroid develop and expand the use of agricultural robots globally.
- The modular FarmDroid FD20 robot can sow, remove weeds, and reduce pesticide usage with a micro-spray system.
- FarmDroid aims to promote sustainable and economically attractive solutions for agriculture.
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The Robot Report
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Chinese AV developer WeRide brings in $458.5M from IPO, private placement
- Chinese AV developer WeRide has been listed on the Nasdaq Global Select Market under the ticker symbol 'WRD'.
- The initial public offering price was set at $15.5 per ADS, resulting in expected proceeds of $458.5 million with concurrent private placement.
- WeRide provides autonomous driving systems ranging from SAE Level 2 to Level 4 and has conducted operations in multiple countries.
- The company's product portfolio includes Robotaxi, Robobus, Robovan, Robosweeper, and an advanced driver-assistance system.
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The Robot Report
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Waymo raises $5.6B to accelerate self-driving car growth
- Waymo raised $5.6 billion in an oversubscribed Series C round.
- The investment will support the expansion of Waymo One robotaxi service.
- Waymo will continue advancing its autonomous driving system, the Waymo Driver.
- Waymo's latest self-driving technology is integrated into Geely's Zeekr vehicles.
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Unite
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Ajay Kumar, CEO of SLK Software – Interview Series
- Ajay Kumar, the CEO of SLK Software, is passionate about growing and scaling the business performance and giving back to the community.
- SLK Software’s EverythingAI platform consists of specialized AI solutions for banking, insurance, and manufacturing industries to drive efficiency, accuracy, and innovation.
- SLK Software’s Data Artistry feature simplifies data comprehension with automated data exploration and profiling, AI-powered model building, and interactive visualizations and reports.
- SLK Software’s QuoteAI tool employs advanced AI technologies for automated data extraction, sufficiency validation, quote generation, and follow-up automation to streamline quoting processes for businesses.
- SLK Software’s SentiX leverages advanced sentiment analysis technology to provide businesses with actionable insights from customer feedback and reviews, improving customer experiences and driving data-driven decisions.
- SLK Software's EverythingAI platform offers comprehensive AI solutions, platforms, and accelerators that equip businesses with the resources to transition smoothly into the AI-led enterprise and overcome AI adoption challenges.
- SLK Software's AI-powered solutions like TrackShieldAI and PeakPerform play distinct yet critical roles in driving efficiency and productivity in the manufacturing industry.
- SLK Software ensures responsible AI implementation in regulated industries like finance and insurance through compliance with regulations, explainability and transparency, ethical AI framework, human oversight and governance, and risk management & monitoring.
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Unite
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AI in the Clinical Setting: Understanding Nurses’ Skepticism and Finding the Way Forward
- AI adoption is becoming increasingly prevalent in clinical settings and is here to stay.
- Many clinicians, including nurses, are wary of using AI platforms specifically designed to improve the clinician experience.
- Nurses protest the health system’s use of ‘untested’ AI tools and request to be a part of AI development process.
- The fear that AI will be used in place of nurses and lead to shifts in staffing numbers is causing apprehension in the profession.
- Automated solutions may lead to resistance from nurses who are worried about job security amidst pervasive workforce deficits.
- AI-generated errors in healthcare are unpredictable and tend to have a higher margin of error, making them difficult to rectify quickly, potentially leading to patient harm.
- Nurses feel personally responsible for maintaining patient confidentiality, and any lapses due to technological vulnerabilities are completely unacceptable.
- AI can tackle mundane, routine duties that hold clinicians back, providing them with increased bandwidth centered around direct patient care.
- VR training has been proven to enhance learners’ surgical performance by 230%.
- Given these hesitations both AI-enabled practices in healthcare and nursing must take a cautious approach collaborating with nurses to increase user accessibility and make a positive impact on nurse sentiment towards AI.
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The Robot Report
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New incubator Reservoir Farms to cultivate agrobotics startups
- Reservoir Farms, a nonprofit tech incubator in California, is launching an on-farm robotics incubator called Reservoir Farms.
- Reservoir Farms will provide test fields, assembly workshops, tools, and storage for agrobotics startups.
- The incubator aims to accelerate the development of agricultural innovations in automation and robotics, specifically for specialty crop farms in California.
- Key industry sponsors include Western Growers Association, UC ANR, and HawkTower.
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The Robot Report
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Nimble picks up $106M to scale general purpose fulfillment robot
- Nimble, an AI-powered fulfillment robot company, has closed a $106 million Series C funding round led by FedEx Corp.
- Nimble aims to revolutionize warehouse automation through turnkey autonomous fulfillment centers powered by general-purpose warehouse robots.
- The company's intelligent robots can handle core fulfillment tasks, including picking, packing, sorting, and storage and retrieval.
- The funding will be used to scale robot manufacturing, system deployments, and further research and development into autonomous logistics.
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