Orby has now joined Databricks’ Built On Partner Program and is leveraging Databricks Mosaic AI to pretrain, build, deploy and monitor its innovative Large Action Model, ActIO, a deep learning model able to interpret actions and perform complex tasks based on user inputs.

“As the demand for data intelligence increases, Orby’s AI innovations are a real game changer in enabling enterprise automations that require truly cognizant reasoning,” said Naveen Rao, VP of Generative AI at Databricks.

“Orby’s unique LAM approach gives organizations the ability to complete tasks with increasing complexity and variability, easily automating complex tasks that, until now, just hasn’t been possible or practical,” Rao concluded.

LARGE ACTION MODEL TAKING CENTER STAGE

Unlike conventional Large Language Model (LLMs) approaches, which focus on interpreting language and generating responses, Orby’s unique Large Action Model (LAM), observes actions to automate tasks and make decisions.

Orby’s LAM simply observes a user at work, learns what can be automated, and creates the actions to implement it. Users then approve the process and can modify the actions at any time, this allows continuous improvement as Orby learns more.

Making generative AI truly useful for the enterprise requires incredible amounts of variable inputs to enable rapid contextual reasoning. Today’s open source and proprietary LLMs are trained on massive amounts of data, but of only one modality: language. Other multimodal models may allow for variable inputs but lack the complex planning and visual grounding capabilities necessary to translate these inputs into enterprise-ready actions that reason, adjust, continuously learn and improve. Large Action Models are uniquely suited to empower enterprise efficiency, but first must be trained on massive amounts of data across multiple modalities.

“Databricks Mosaic AI makes it possible to build a multimodal training pipeline at a scale that is essential for delivering unrivaled performance, accuracy and stability,” said Will Lu, Co-Founder and CTO of Orby.

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The autoSCORE application was developed in Norway by Holberg EEG using a deep-learning model and trained on the world’s largest dataset of more than 30,000 expertly labeled EEG recordings. The development and validation of the model have been carefully designed to avoid typical errors and sources of bias, and the output is focused on aspects key to the interpretation of clinical EEGs [1].

“The development of the world’s first AI model capable of reading clinical EEGs at the level of the best experts in the world is a significant accomplishment,” says Harald Aurlien, co-founder of Holberg EEG and a consultant in clinical neurophysiology at Haukeland University Hospital. “The partnership and distribution agreement with Natus, one of the world’s largest EEG companies, will help bring this innovative solution to customers around the world.”

The 2023 study “Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence,” published in JAMA, revealed autoSCORE consistently performed with accuracy, sensitivity, and specificity near or above 90% [1]. It also showed the autoSCORE application to be on par with leading human experts while outperforming similar AI models on the market.

“The autoSCORE application has the potential to improve clinical outcomes and value of care for the millions suffering from epilepsy,” states Natus Neuro Chief Executive Officer Chris Landon. “This newly launched solution represents the first of what we expect will be a series of innovative AI applications at Natus designed to deliver efficiency and quality improvements across healthcare.”

Visual EEG review is considered the gold standard for determining abnormalities, but it demands clinical resources and years of specialized training. The AI-enabled autoSCORE application is designed to allow neurocare teams to more efficiently and consistently perform EEG data analysis.

Unlike traditional spike and seizure detectors, the autoSCORE application comprehensively assesses EEG data for multiple clinically relevant abnormalities and provides study-level assessments to inform care teams whether an EEG study is normal or abnormal.

The autoSCORE application has received U.S. Food and Drug Administration clearance for use with routine EEG studies and is currently available in the United States, exclusively with Natus NeuroWorks EEG Software Version 10.

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By joining NVIDIA Inception, Mendel will receive access to NVIDIA’s industry-leading technology, including the latest NVIDIA NIM inference microservices to accelerate Mendel’s Hypercube AI solution, and technical expertise in artificial intelligence, deep learning and data science. The resources from the program will help Mendel bring sophisticated, reliable and explainable AI solutions to the healthcare sector that are not only powerful but also responsible and tailored to meet the high stakes of medical decision-making.

“We are incredibly excited to share that Mendel AI has joined NVIDIA Inception, marking a significant milestone in our ongoing efforts to redefine the possibilities of AI in healthcare,” said Karim Galil, CEO of Mendel AI. “By integrating NVIDIA’s cutting-edge AI tools, we aim to enhance our platform’s capabilities, specifically in processing and understanding complex, unstructured medical data at an unprecedented scale. With the program’s resources and together with other forward-thinking companies, we are committed to pushing the boundaries of what AI can achieve in medical research and patient care, aiming to ensure that our technology continues to lead the way in efficiency and effectiveness.”

Mendel’s innovative approach to creating clinician-like AI was included in a recent NVIDIA blog post, highlighting Mendel’s applications across clinical research, real-world evidence generation and cohort selection.

NVIDIA Inception helps startups during critical stages of product development, prototyping and deployment. Every Inception member gets a custom set of ongoing benefits, such as NVIDIA Training credits, preferred pricing on NVIDIA hardware and software, and technological assistance, which provides startups with the fundamental tools to help them grow.

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Key Features of Image-Pro AI:

• Superior outline accuracy: Even the most complicated edges can be traced with high quality. AI Models work similar to the human brain, finding objects undeterred by dim, complex edges.
• User-friendly operation: AI Deep Learning Segmentation requires minimal input to operate efficiently. Simple controls, limited options, and fast prediction results.
• Secure & confidential: No uploading or downloading required. Save time and avoid sharing your data on unsecure company servers. All operations are on-device.
• Protocol-ready: Integrate Deep Learning Segmentation accuracy into an automated workflow by saving an Analysis Protocol with a custom or pre-trained model.

Tailored for both life sciences and materials research and quality inspection, Image-Pro® AI offers robust solutions that cater to specific application needs. Trusted globally, Image-Pro® AI represents a significant leap forward in scientific image analysis, providing a comprehensive, user-friendly tool for researchers and scientists.

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Frazier continues to focus on the strategic expansion of its dedicated Center of Excellence (CoE), providing Fortune 500 talent to our portfolio companies in the areas of Human Capital, Technology & Innovation, Data Analytics & Artificial Intelligence, M&A & Corporate Development, Finance, Operations, Legal, Commercial Excellence, and ESG. Frazier Managing Partner Ben Magnano said, “As the firm continues to invest in the breadth and depth of this team, we are targeting expansion in areas where we see accelerated value creation opportunities as part of our differentiated strategy.”

“Frazier is fortunate to have such a talented, collaborative group of professionals who enjoy supporting our management teams and helping them drive transformation,” said Andy Caine, CoE COO & Partner. “We are thrilled to welcome Sanji, Steve, and Lindsey to our team, each of whom brings a wealth of experience in their areas of expertise.”

About Sanji Fernando: Sanji joined Frazier’s CoE Data & AI team after serving as SVP of AI Products and Platforms at Optum, where he spearheaded the development of next generation AI to transform healthcare. He launched United AI Studio, a unified platform enabling rapid experimentation and deployment of advanced ML across UHC and Optum. The United AI Studio provides access to cutting-edge capabilities like Generative AI while ensuring rigorous monitoring of model performance and evaluating models for bias. Previously, Sanji pioneered the application of deep learning for risk adjustment, automating the identification of hierarchical condition codes from medical charts. This innovation drove efficiencies and positioned UnitedHealth as an AI leader in healthcare administration. Sanji also founded Optum Labs’ Center for Applied Data Science (CADS), delivering innovative AI and Machine Learning solutions to complex healthcare challenges. With his proven track record of leveraging AI to create enterprise value, Sanji was key in positioning UnitedHealth to the forefront of healthcare’s digital transformation. His leadership and technical acumen make him a strategic driver of transformative innovation for the organization. Sanji obtained his BS in Computer Science from Trinity College in Hartford.

About Steve Blackhart: Steve Blackhart is an M&A professional with extensive transaction experience on both the buy-side and sell-side. He joins Frazier from Black Eagle Advisors, an M&A advisory firm he founded in 2015. There, Steve executed transactions across a wide breadth of industries, including healthcare, business services, and consumer products. He also provided strategic guidance in the formation of corporate development functions within newly acquisitive organizations and served as the head of M&A for a number of companies. Most recently, Steve led corporate development for MiX Telematics (NYSE: MIXT), directing the Company’s acquisition of Trimble’s Field Services Management division and its merger with Powerfleet (NASDAQ: PWFL). Steve began his career in the investment banking division of Bank of America Merrill Lynch before becoming a private equity professional at FFL Partners. At FFL, Steve was involved in the firm’s investments in healthcare, consumer products, and financial services businesses. Steve holds a BS in Business Administration from the University of Southern California and an MBA from Harvard Business School.

About Lindsey Murphy: Lindsey has over 12 years of experience in sales operations, and in her role at Frazier, she will support its portfolio companies with sales operations, including improving sales processes, tools, and pipeline management. Her responsibilities include utilizing expertise in data analysis, CRM administration, and sales forecasting to improve sales efficiency and revenue growth. Prior to Frazier, she was the Director of Sales Operations at Parata, a Frazier portfolio company. During her time at Parata, Lindsey provided strategy, design, and execution of sales processes for the commercial organization leading to increasing revenue from $75 million to $275 million. Lindsey received her BS in Business Administration from the University of North Carolina, Wilmington.

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KAYTUS, a leading IT infrastructure provider, has unveiled MotusAI, an AI development platform now accessible for trial worldwide. MotusAI is tailored for deep learning and AI development, integrating GPU and data resources alongside AI development environments to streamline computing resource allocation, task orchestration, and centralized management. It accelerates training data and manages AI model development workflows seamlessly. This platform drastically reduces resource investment, boosts development efficiency, elevates cluster computing power utilization to over 70%, and significantly enhance in large-scale training task scheduling performance.

Streamline AI Development for Cost-Effectiveness and Efficiency

The rapid expansion of enterprise AI business and AI model development brings forth challenges including low computing efficiency, complexity in model development, varied requirements for task orchestration across different scenarios, and unstable computing resources. Ensuring efficient, flexible, and stable operation of AI business is critical for enterprises to consistently derive business insights, generate revenue, and maintain competitiveness.

Optimize Resource Management for Maximum Computing Power

MotusAI efficiently allocates resources and workloads by implementing intelligent and flexible GPU scheduling. It caters to diverse AI workload demands for computing power by dynamically allocating GPU resources based on demand. With multi-dimensional and dynamic GPU resource allocation, including fine-grained GPU scheduling and support for Multi-Instance GPU (MIG), MotusAI effectively meets computing power requirements across various scenarios such as model development, debugging, and training.

Streamline Task Orchestration for Versatile Support of Various Scenario

MotusAI has revolutionized cloud-native scheduling systems. Its scheduler surpasses the community version by dramatically improving the scheduling performance of large-scale POD tasks. MotusAI achieves rapid startup and environment readiness for hundreds of PODs, boasting a five times increase in throughput and a five times decrease in latency compared to the community scheduler. This ensures efficient scheduling and utilization of computing resources for large-scale training. Moreover, MotusAI enables dynamic scaling of AI workloads for both training and inference services, supporting burst tasks and fulfilling diverse scheduling needs across various scenarios.

MotusAI empowers users to maximize computing resources, spanning from fine-grained division of single-card multiple instances to large-scale parallel computing across multiple machines and cards. By integrating features like computing power pooling, dynamic scaling, and GPU single-card reuse, MotusAI significantly enhances computing power utilization, achieving an average utilization rate of over 70%. Furthermore, it enhances computing efficiency by leveraging cluster topology awareness and optimizing network communication.

Data Transfer Acceleration for Three Times Efficiency Improvement

MotusAI excels in data transfer acceleration through innovative features such as supporting local loading and computing of remote data, which eliminates delays caused by network I/O during computation. Utilizing strategies like “zero-copy” data transfer, multi-threaded retrieval, incremental data updates, and affinity scheduling, MotusAI significantly reduces data caching cycles. These enhancements greatly improve AI development and training efficiency, resulting in 2-3 times boost in model efficiency during data training.

Reliable, and Automatically Fault-Tolerant Platform

MotusAI supports performance monitoring and alerts for computing resources, providing real-time status updates for core platform services. It employs sandbox isolation mechanisms for data with higher security levels. In case of resource failures or abnormalities, MotusAI automatically initiates fault tolerance processes to ensure the quickest possible recovery during interrupted training tasks. This approach reduces fault handling time by over 90%, on average.

Comprehensive Management of AI Model Development in One Integrated Solution

MotusAI accelerates AI development and supports every stage of large model development. From managing data samples and software stacks to designing model architectures, debugging code, training models, tuning parameters, and conducting evaluation testing, MotusAI offers a complete platform. It integrates popular development frameworks like PyTorch and TensorFlow, along with distributed training frameworks such as Megatron and DeepSpeed.

Moreover, MotusAI enables comprehensive lifecycle management of AI inferencing services, including offline and online testing, A/B testing, rolling release, service orchestration, and service decommissioning. These features collectively enhance the business value of AI technology, fostering continuous business growth.

Additionally, MotusAI provides an integrated visual management and operation interface that covers computing, networking, storage, and application resources. Operational staff can comprehensively manage, monitor, and evaluate the overall platform operation status through a single interface.

Free Trial Available

MotusAI is now available worldwide for a trial period, offering free remote access for one month, along with testing, training, and support. Users can also opt for local deployment using their own devices and environment, with local deployment testing support from KAYTUS. For more information¹ and to register², please visit Link¹,Link².

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Integrating Sony’s Image Sensor Models into Anyverse’s platform will revolutionize perception system design and validation cycles, allowing developers to evaluate sensor configurations and increase model performance before implementation. Leveraging Anyverse’s hyperspectral rendering technology, the collaboration ensures the generation of highly accurate synthetic data and physically-based sensor simulation, now enhanced by Sony’s Image Sensor Models.

“The collaboration with Sony Semiconductor Solutions represents a tremendous leap forward in addressing one of the most critical challenges in dataset creation – the perception domain gap,” said Víctor González, CEO at Anyverse. “By bridging this gap through the combination of high-fidelity data and physical sensor simulation, we empower developers to create deep learning models that can effectively handle a wide spectrum of real-world scenarios.”

The perception domain gap refers to the variance between the characteristics of the sensors utilized in data acquisition and those deployed in production systems. This variance can significantly impact the performance of deep learning models, hindering their ability to interpret data accurately. With Anyverse’s platform enriched by Sony’s Image Sensor Models, developers can now mitigate this challenge, ensuring seamless integration of new data into production systems.

This collaboration reduces the industry’s reliance on real-world data collection, streamlining go-to-market timelines and minimizing costs associated with physical testing. Developers no longer need to deploy sensors on numerous vehicles/devices for testing purposes; instead, they can access high-quality data and sensor models through Anyverse’s platform, expediting the system’s evaluation process or expanding the perception model’s coverage.

“The collaboration between Anyverse and Sony Semiconductor Solutions will provide an automotive-grade end-to-end spectral simulation pipeline to the ADAS perception system developers,” said Tomoki Seita, General Manager, Automotive Business Division, Sony Semiconductor Solutions Corporation. “Sony has prepared Image Sensor Models based on the internal architecture of the image sensors used in camera systems to achieve automotive-grade fidelity.”

Through this technical collaboration, Anyverse and Sony reaffirm their commitment to driving innovation in autonomous systems and shaping the future of advanced perception. For more information, visit https://anyverse.ai/ and https://www.sony-semicon.com/en/.

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Working in digital and data transformation for more than 25 years, Zutavern joins us with extensive experience successfully leading and advising companies for strategy and growth. She is currently Partner and Managing Director at AlixPartners, a financial advisory and global consulting firm specializing in digital, technology and accelerated business transformation, where she leads the firm’s Global artificial intelligence (AI) business.

Angela has led AI research and development efforts, including breakthroughs in quantum machine learning, deep learning, computer vision, and other key technologies. She also advised federal agencies on cybersecurity vulnerability detection and mitigation, worked with the Department of Homeland Security Cybersecurity and Infrastructure Security Agency to define cybersecurity standards, advised the Homeland Security Investigations Cyber Crimes Center, and helped Fortune 500 and Global 2000 companies assess and address cybersecurity risks and respond to incidents. Previously, she helped establish and lead the Data Science practice and Strategic Innovation Group at Booz Allen Hamilton.

In addition to her professional work experience, Angela is the author of the bestselling book, the Mathematical Corporation: Where Machine Intelligence and Human Ingenuity Achieve the Impossible. A frequent speaker on the power of AI and digital transformation, she has been featured on NBC’s TODAY show and in the New York Times, Wall Street Journal, MIT Sloan Management Review, Stanford Social Innovation Review, and other publications. She has authored numerous articles and the academic paper ‘Building an Artificial Intelligence Explanation Capability’. Angela is also the recipient of the Lifetime Achievement Award for Women in Technology form Consulting Magazine.

Angela holds an MBA from Southern Methodist University and Bachelor of Science in Industrial and Systems Engineering from Virginia Tech.

CDM Smith is a privately owned engineering and construction firm providing legendary client service and smart solutions in water, environment, transportation, energy and facilities. Passionate about our work and invested in each other, we are inspired to think and driven to solve the world’s environmental and infrastructure challenges.

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‘3D Perception Network’ represents STRADVISION’s latest advancement in perception technology. It refines the sensing-perceiving-planning-action sequence, providing more reliable ADAS solutions. The 3D Perception Network achieves better performance by reducing detection errors by up to 10% and improves detection stability by up to 30%, and greatly enhances the scalability and cost efficiency of the ADAS/AD technology in passenger vehicles.

The partnership was founded on a shared vision to provide high-quality and cost-efficient driving solutions and is advancing toward a promising business opportunity. The successful optimization of SVNet 3D Perception Network on Journey 3 marks another technological milestone and establishes a straightforward path for a swift and seamless transition to the upcoming Horizon Journey 6. The Horizon Journey 6 series, equipped with Nash BPU architecture, offers unmatched energy efficiency and openness.

The adaptable and scalable joint solution by STRADVISION and Horizon Robotics continues to lead the market in terms of performance, low system complexity, and cost-effectiveness, paving the way for expanded mass-market production of L2/L2+ ADAS systems, and bringing safe, comfortable, and enjoyable driving experiences to consumers.

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Argo Translation, a Chicago-based language services company, announced today the launch of its latest innovative service offering: AI-driven translation. The solution creates custom AI models with each customer’s propriety content and delivers unparalleled accuracy and fluency, transforming how businesses communicate across global markets.

Created by applying the recent advancements in AI and deep learning, Argo Translation’s semi-custom to fully trained AI-driven translation models offer accurate, context-aware translations, enabling businesses of any size and budget to effortlessly engage with a global audience.

Argo Translation’s 29 years of expertise allow the language service provider to fuse decades-long human translation insights with cutting-edge AI technology to develop highly specialized models that not only understand the nuances of language but also reflect the specific terminology, tone, and stylistic preferences unique to each customer’s domain. The AI-optimized workflow also allows for human post-editing options that can further increase quality while taking a fraction of a human translator’s time.

Peter Argondizzo, co-founder of Argo Translation, shares, “We’ve already created AI models for some of our largest customers, and the results have been outstanding. This translation technology is truly game-changing; the optimal intersection between AI, legacy translation work, and solid editing is finally here.”

This revolutionary approach empowers customers to benefit from a translation solution deeply rooted in the rich linguistic expertise of the past, yet fully equipped to meet the dynamic demands of the future.

Learn more about AI-driven translation at argotrans.com/technology/ai-driven-translation.

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