GENERAL AI

Smartlogic releases next-gen semantic AI platform

Smartlogic | March 25, 2022

Smartlogic, the leading Semantic AI technology, announced the release of Semaphore 5.4. 0, which contain additions and improvements across many Semaphore models.

Model, scale, and collaborate; auto-classification, fact and language services; and integrate and visualize - in a modular and adaptable platform that lets organizations add capabilities as their business needs evolve.

“Semaphore 5.4.0 focuses on product updates that include market demands and customer feedback to ensure value-driven improvements across all Semaphore modules. Semaphore incorporates innovative technologies and strategies to deliver a unified user experience, enhanced interoperability, and flexible integration within your ecosystem for quality data-driven outcomes.”

Matthieu Jonglez, CTO Smartlogic

Highlights of Semaphore 5.4.0

Advanced knowledge model development capabilities
  • New linked data, mapping, and reconciliation service
  • Enhanced text analytics and model enrichment support

Model development with subject matter specialists
  • State-of-the-art implementation of Semaphore knowledge review tool (KRT) that extends development and collaboration capabilities
  • Selective task management that supports commits and rollbacks

Auto-classification, facts, and language services
  • Precision and recall capabilities incorporated into the user interface
  • Extensions to the fact extraction framework
  • Publishing optimization enhancement

Semaphore accumulates the power of Semantic AI with industry-recognized knowledge model management, precise, complete, and consistent classification and language services, and cutting-edge fact extraction capabilities to help organizations to make smarter decisions. It is designed for the world’s largest enterprise that demands scale and quality.

Semaphore adds value to enterprise projects that call for the aggressive use of data, both organized and unstructured, both internally and externally. In addition, it serves as the core for cognitive applications, including intelligent contextual search, enriched process automation, relevant recommendation engines, customer experience, regulatory compliance, contract lifecycle management, and data security.

Spotlight

Cloud computing gets a lot of attention, and for good reason: it’s where much of IT is going. But on-premises datacenters also have an important role to play, both today and in the future. For many organizations, integrating these two to create a hybrid cloud is essential. Microsoft understands this reality. To help you achieve it, we offer a broad range of cloud and on-premises technologies that work together in a coherent way. And unlike our competitors, we provide the flexibility to let you choose the path that’s right for you.


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SOFTWARE

Sirona Medical Acquires Nines and Key Personnel

Sirona Medical | February 21, 2022

Sirona Medical, a software company founded on a deep understanding of both the practice and business of radiology, today announced the acquisition of Nines' AI capabilities, including its clinical data pipeline, machine learning engines, AI powered radiology workflow management and analytics tools, as well as two FDA-cleared medical devices. In addition, key personnel from Nines will join Sirona Medical, including Maureen Bradford, as chief revenue officer. The FDA-cleared medical devices, NinesMeasure™, a lung nodule algorithm that leverages AI to accelerate the diagnoses of certain respiratory diseases, and NinesAI™ Emergent Triage, a set of AI-powered algorithms that triages time-critical, life-threatening indications of intracranial hemorrhage and mass effect, will be integrated into Sirona's radiology operating system (RadOS), a unified platform that combines siloed radiology applications into a cohesive user experience. The inspiration for Nines has always been to leverage the latest AI capabilities and use that to transform radiology for the better, Over the past several years, Nines made tremendous progress from a technology standpoint. I am thrilled that Nines' innovations will be integrated into Sirona's impressive RadOS to accelerate their fantastic mission, clients, and team." David Stavens, former CEO of Nines. The acquisition comes on the heels of Sirona's strategic partnership with RevealDx to integrate their CE-marked RevealAI-Lung algorithm into Sirona's RadOS platform and marks another key milestone in Sirona's commercial rollout of delivering novel value to its radiology customers. In order for AI adoption to take place at scale, you need to break down the artificial silos of a medical image viewer, studies worklist, and speech recognition reporter. It's only through a unified platform that AI can take full advantage of the underlying data and deliver context-specific results in the most relevant way to radiologists, I've been a longtime fan of what Nines has built and we're excited to add their brilliant minds to the team, as we continue to expand on our vision to help radiologists through better software." Cameron Andrews, founder and CEO of Sirona Medical. Sirona Medical did not acquire Nines' teleradiology business, Nines Radiology. The terms of the deal were not disclosed. About Sirona Medical Inc. Sirona Medical Inc. is addressing the needs of today's radiology practices with a novel cloud-native platform that unifies radiology IT applications – worklist, viewer, reporter, and AI – onto a single, streamlined Workspace. Sirona's radiology operating system (RadOS) puts radiologists in the driver's seat with novel AI-powered solutions that simplify their workflow and amplify their work product. Based in San Francisco, CA, Sirona Medical is founded on a deep understanding of both the practice and business of radiology, with the goal of enabling radiologists to work as fast as they can think.

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GENERAL AI

Deci Launches Version 2.0 of its Deep Learning Development Platform, to Democratize the Power of NAS and Eliminate the AI Efficiency Gap

Deci | May 13, 2022

Deci, the deep learning company harnessing AI to build AI, today launched Version 2.0 of its deep learning development platform, making it easier than ever before for AI developers to build, optimize, and deploy computer vision models on any hardware and environment including cloud, edge and mobile with outstanding accuracy and runtime performance. AI developers face an uphill struggle developing production-ready deep learning models for deployment. These challenges can be largely attributed to the AI efficiency gap facing the industry in which algorithms are growing more powerful and complex, but available compute power is not keeping pace. This gap also creates financial barriers by making the deep learning development and processing more cumbersome and expensive. While Neural Architecture Search (NAS) has been presented as a potential solution to automate the design of superior artificial neural networks that can outperform manually-designed architectures, the resource requirements to operate such technology is excessive. To date, NAS has only been successfully implemented by tech giants like Google, Microsoft and in the confines of academia, proving its impracticality for the vast majority of developers. In order to solve this problem, Deci’s platform, powered by its proprietary NAS engine called AutoNAC (Automated Neural Architecture Construction), enables AI developers to automatically and affordably build efficient computer vision models that deliver the highest accuracy for any given inference hardware, speed, size and targets. Models generated by Deci outperform other known state-of-the-art (SOTA) architectures by a factor of 3x-10x. Developers can start their projects with pre-trained and optimized models (DeciNets) that were generated by the AutoNAC engine for a wide range of hardware and computer vision tasks or use the AutoNAC engine to generate more custom architectures that are tailored for their specific use-cases. In addition, the platform supports teams with a wide range of tools required to develop deep learning-based applications including a hardware-aware model zoo to easily select and benchmark models and hardware, SuperGradients - an open source training library with proven recipes for faster training, automated runtime optimizations, model packaging and more. By using Deci’s platform, AI developers achieve improved inference performance and efficiency to enable deployment on resource constrained edge devices, maximize hardware utilization and reduce training and inference cost. The entire development cycle is shortened and the uncertainty of how the model will deploy on the inference hardware is eliminated. “The new version of Deci’s deep learning platform makes hardware-aware NAS technology accessible to AI teams of any size, helping them eliminate complexities and focus on what they do best - build innovative computer vision applications. We take pride in the fact that the deep learning models generated by Deci's platform are powering AI-based applications of some of the leading enterprises worldwide. We are excited to unleash this powerful engine to help make computer vision even more widely available. Only then can we truly achieve a world where AI advances humanity without limitations, finally making AI affordable, accessible and scalable for all.” Yonatan Geifman, co-founder and CEO of Deci With Deci’s Version 2.0 platform, AI developers can: Easily benchmark models and inference hardware: With Deci’s hardware-aware model zoo, developers can quickly measure inference time of pre-trained and optimized models on and various hardware including edge devices via Deci’s SaaS platform. Simplify the hardware and model selection process by eliminating the need to manually setup and test various combinations of models and hardware. Generate Tailored SOTA CNN Architectures: Automatically find accurate & efficient architectures tailored for the application, hardware and performance targets with Deci’s AutoNAC engine. Simplify Training with SuperGradients: Leverage proven hyperparameter recipes and with Deci’s PyTorch based open source training library called SuperGradients. Automated Runtime Optimization: Automatically compile and quantize your models and evaluate different production settings. Deploy with a Few Lines of Code: Developers can deploy their deep learning workloads on any environment with the Deci’s python based inference engine. Deci’s platform includes three tiers: Free Community Tier: For data scientists and ML engineers looking to find the best models, simplify hardware evaluation and boost runtime performance. Professional Tier: For deep learning teams looking to quickly achieve production grade inference performance and shorten development time. Enterprise Tier: For deep learning experts looking to meet specific performance goals for highly customized use cases. About Deci Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company's deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci's proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models' architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci's team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

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SOFTWARE

Prevision.io Announces Support for Third-Party Models with Expert Services Available for Free Benchmark Test

Prevision.io | January 31, 2022

Prevision.io announced—as part of their ongoing Mastering AI Webinar Series—an offering of their resources and expertise for data science teams struggling to deploy models into production. Using the platform's AI infrastructure, the aim is to allow users to test the built-in deployment and monitoring services without a fee and with a fully trained data scientist and a support engineer. During the second episode of the series, Prevision.io executives discussed the current challenges that are plaguing companies' deployment processes. Lack of skills, understaffed IT departments, and widespread ineffectiveness of existing tools/platforms were a few of the issues contributing to high probability of AI project failure. The result: deploying a model can take months or years, but in the webinar, Prevision.io demonstrated that their process can be accomplished in a matter of minutes to hours. Prevision.io's feature-rich platform democratizes AI, empowering teams to deliver projects faster through an intuitive interface that allows users to create, deploy, monitor, and retrain models in a few clicks. As a result, more companies than ever before can bring their models into fruition and keep them in production, scaling the impact of their efforts at a much lower overall cost. From predictive maintenance to fraud detection and warehouse optimization, Prevision.io offers a nearly endless set of features data teams can then customize to fit their needs. We wanted to give data scientists, developers, machine learning engineers, and others the opportunity to use our technology to finish a project that they are struggling with, We want to make their lives easier, and show them a glimpse of what that looks like. By dedicating a few hours of consulting time to each model, we'll evaluate their workflow to allow the prospective user to launch and monitor the model with as few clicks as possible." Tuncay Isik, the founder and CEO of Prevision.io. Prevision.io offers a straightforward solution to simplify the process for its users. Platforms built in the past for data scientists and developers have focused almost exclusively on Fortune 500 companies and data teams with their ability to ink expensive contracts for tools and maintain massive IT footprints. These offerings do not work for the vast majority of users who need a simple solution to deploy their complex workflows. The status quo in our profession is not sustainable as businesses are demanding results from their massive AI and machine learning investments, We intend to enable users to simplify their AI processes so that more projects reach production on time and under budget. We're willing to put our time and resources on the line to make this happen today." Florian Laroumagne, the cofounder and Data Scientist for Prevision.io. About Prevision.io Founded in 2016 by a team of renowned data scientists, Prevision.io brings powerful AI management capabilities to data science users so more AI projects make it into production and stay in production. Prevision.io's purpose-built AI Management Platform was designed by data scientists for data scientists and developers to scale their value, domain expertise, and impact. From banking and financial services to healthcare and retail, data scientists too often lack the tools to create efficient data models. Now with Prevision.io, a member of the Google Cloud Partner Advantage program, data scientists and analysts have the tools they need in one place to build, deploy, monitor, and manage data models across a variety of industries.

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SOFTWARE

RedFlag Mass Notification for Microsoft Teams is now available on Microsoft AppSource

Pocketstop | January 15, 2022

In the event of a critical situation, communicating quickly and effectively to the desired recipients via a multi-channel communication approach is necessary. Within the US, over 700,000 companies use Microsoft 365 which includes Teams as part of its suite of products. Pocketstop is excited to announce the RedFlag + Microsoft Teams integration and a fourth main channel for alerts is now available. By adding the ability to connect via Microsoft Teams in addition to text, voice, and email, RedFlag provides companies an even greater ability to disrupt and ensure the message reaches the intended recipient. Messages sent via RedFlag to Teams are delivered as both a desktop and mobile push notification to their Teams app, no matter their location or device. Leveraging Teams offers the functionality of sending to the other main channels, whether it is a message with links or attachments, adding a conference number to join a call, or an action-based message requiring a response. This is a powerful additional channel to help when time matters, and RedFlag is the only system to send mass notifications via Teams. It is important to communicate to employees the way they consume information. The Teams integration allows us to reach our employees in an additional way, We have some employees that only communicate via Teams, so this ensures our messaging is heard." Will Gott, Human Resource Manager at Wood-Mizer. For more details on the RedFlag + Teams integration, click here, or see the RedFlag listing on Microsoft AppSource. As a Microsoft Silver Partner, The Teams integration deepens RedFlag's existing Microsoft Integration, ensuring Microsoft users can communicate quickly and securely with an ease of setup and integration not available in other platforms. Current Microsoft + RedFlag users are now able to: Extend their reach worldwide via app notifications through the Microsoft Teams app Use the Active Directory sync to automatically import and continuously synchronize recipient data (Coming Soon) Enjoy Single Sign On for ease of use and security Quickly send multi-channel messages right within Outlook via the add-in Be confident in security, reliability, and scalability because RedFlag is built on Microsoft Azure About Pocketstop Pocketstop is a communication software solutions company empowering companies to create personalized, automated messages designed to provide rapid ROI, backed by the industry's best support at a cost customers can afford.

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Spotlight

Cloud computing gets a lot of attention, and for good reason: it’s where much of IT is going. But on-premises datacenters also have an important role to play, both today and in the future. For many organizations, integrating these two to create a hybrid cloud is essential. Microsoft understands this reality. To help you achieve it, we offer a broad range of cloud and on-premises technologies that work together in a coherent way. And unlike our competitors, we provide the flexibility to let you choose the path that’s right for you.

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