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Algorithms have always been at home in the digital world, where they are trained and developed in perfectly simulated environments. The current wave of deep learning facilitates AIs leap from the digital to the physical world. The applications are endless, from manufacturing to agriculture, but there are still hurdles to overcome.

To traditional AI specialists, deep learning (DL) is old hat. It got its breakthrough in 2012 when Alex Krizhevsky successfully deployed convolutional neural networks, the hallmark of deep learning technology, for the first time with his AlexNet algorithm. Its neural networks that have allowed computers to see, hear and speak. DL is the reason we can talk to our phones and dictate emails to our computers. Yet DL algorithms have always played their part in the safe simulated environment of the digital world. Pioneer AI researchers are working hard to introduce deep learning to our physical, three-dimensional world. Yep, the real world.

Deep learning could do much to improve your business, whether you are a car manufacturer, a chipmaker or a farmer. Although the technology has matured, the leap from the digital to the physical world has proven to be more challenging than many expected. This is why weve been talking about smart refrigerators doing our shopping for years, but no one actually has one yet. When algorithms leave their cozy digital nests and have to fend for themselves in three very real and raw dimensions there is more than one challenge to be overcome.

The first problem is accuracy. In the digital world, algorithms can get away with accuracies of around 80%. That doesnt quite cut it in the real world. If a tomato harvesting robot sees only 80% of all tomatoes, the grower will miss 20% of his turnover, says Albert van Breemen, a Dutch AI researcher who has developed DL algorithms for agriculture and horticulture in The Netherlands. His AI solutions include a robot that cuts leaves of cucumber plants, an asparagus harvesting robot and a model that predicts strawberry harvests. His company is also active in the medical manufacturing world, where his team created a model that optimizes the production of medical isotopes. My customers are used to 99.9% accuracy and they expect AI to do the same, Van Breemen says. Every percent of accuracy loss is going to cost them money.

To achieve the desired levels, AI models have to be retrained all the time, which requires a flow of constantly updated data. Data collection is both expensive and time-consuming, as all that data has to be annotated by humans. To solve that challenge Van Breemen has outfitted each of his robots with functionality that lets it know when it is performing either well or badly. When making mistakes the robots will upload only the specific data where they need to improve. That data is collected automatically across the entire robot fleet. So instead of receiving thousands of images, Van Breemens team only gets a hundred or so, that are then labeled and tagged and sent back to the robots for retraining. A few years ago everybody said that data is gold, he says. Now we see that data is actually a huge haystack hiding a nugget of gold. So the challenge is not just collecting lots of data, but the right kind of data.

His team has developed software that automates the retraining of new experiences. Their AI models can now train for new environments on their own, effectively cutting out the human from the loop. Theyve also found a way to automate the annotation process by training an AI model to do much of the annotation work for them. Van Breemen: Its somewhat paradoxical because you could argue that a model that can annotate photos is the same model I need for my application. But we train our annotation model with a much smaller data size than our goal model. The annotation model is less accurate and can still make mistakes, but its good enough to create new data points we can use to automate the annotation process.

The Dutch AI specialist sees a huge potential for deep learning in the manufacturing industry, where AI could be used for applications like defect detection and machine optimization. The global smart manufacturing industry is currently valued at 198 billion dollars and has a predicted growth rate of 11% until 2025. The Brainport region around the city of Eindhoven where Van Breemens company is headquartered is teeming with world-class manufacturing corporates, such as Philips and ASML. (Van Breemen has worked for both companies in the past.)

A second challenge of applying AI in the real world is the fact that physical environments are much more varied and complex than digital ones. A self-driving car that is trained in the US will not automatically work in Europe with its different traffic rules and signs. Van Breemen faced this challenge when he had to apply his DL model that cuts cucumber plant leaves to a different growers greenhouse. If this took place in the digital world I would just take the same model and train it with the data from the new grower, he says. But this particular grower operated his greenhouse with LED lighting, which gave all the cucumber images a bluish-purple glow our model didnt recognize. So we had to adapt the model to correct for this real-world deviation. There are all these unexpected things that happen when you take your models out of the digital world and apply them to the real world.

Van Breemen calls this the sim-to-real gap, the disparity between a predictable and unchanging simulated environment and the unpredictable, ever-changing physical reality. Andrew Ng, the renowned AI researcher from Stanford and cofounder of Google Brain who also seeks to apply deep learning to manufacturing, speaks of the proof of concept to production gap. Its one of the reasons why 75% of all AI projects in manufacturing fail to launch. According to Ng paying more attention to cleaning up your data set is one way to solve the problem. The traditional view in AI was to focus on building a good model and let the model deal with noise in the data. However, in manufacturing a data-centric view may be more useful, since the data set size is often small. Improving data will then immediately have an effect on improving the overall accuracy of the model.

Apart from cleaner data, another way to bridge the sim-to-real gap is by using cycleGAN, an image translation technique that connects two different domains, made popular by aging apps like FaceApp. Van Breemens team researched cycleGAN for its application in manufacturing environments. The team trained a model that optimized the movements of a robotic arm in a simulated environment, where three simulated cameras observed a simulated robotic arm picking up a simulated object. They then developed a DL algorithm based on cycleGAN that translated the images from the real world (three real cameras observing a real robotic arm picking up a real object) to a simulated image, which could then be used to retrain the simulated model. Van Breemen: A robotic arm has a lot of moving parts. Normally you would have to program all those movements beforehand. But if you give it a clearly described goal, such as picking up an object, it will now optimize the movements in the simulated world first. Through cycleGAN you can then use that optimization in the real world, which saves a lot of man-hours. Each separate factory using the same AI model to operate a robotic arm would have to train its own cycleGAN to tweak the generic model to suit its own specific real-world parameters.

The field of deep learning continues to grow and develop. Its new frontier is called reinforcement learning. This is where algorithms change from mere observers to decision-makers, giving robots instructions on how to work more efficiently. Standard DL algorithms are programmed by software engineers to perform a specific task, like moving a robotic arm to fold a box. A reinforcement algorithm could find out there are more efficient ways to fold boxes outside of their preprogrammed range.

It was reinforcement learning (RL) that made an AI system beat the worlds best Go player back in 2016. Now RL is also slowly making its way into manufacturing. The technology isnt mature enough to be deployed just yet, but according to the experts, this will only be a matter of time.

With the help of RL, Albert Van Breemen envisions optimizing an entire greenhouse. This is done by letting the AI system decide how the plants can grow in the most efficient way for the grower to maximize profit. The optimization process takes place in a simulated environment, where thousands of possible growth scenarios are tried out. The simulation plays around with different growth variables like temperature, humidity, lighting and fertilizer, and then chooses the scenario where the plants grow best. The winning scenario is then translated back to the three-dimensional world of a real greenhouse. The bottleneck is the sim-to-real gap, Van Breemen explains. But I really expect those problems to be solved in the next five to ten years.

As a trained psychologist I am fascinated by the transition AI is making from the digital to the physical world. It goes to show how complex our three-dimensional world really is and how much neurological and mechanical skill is needed for simple actions like cutting leaves or folding boxes. This transition is making us more aware of our own internal, brain-operated algorithms that help us navigate the world and which have taken millennia to develop. Itll be interesting to see how AI is going to compete with that. And if AI eventually catches up, Im sure my smart refrigerator will order champagne to celebrate.

Bert-Jan Woertman is the director of Mikrocentrum.

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IonQ and Hyundai have partnered to apply Quantum ML to automotive recognition of traffic signals and ... [+] other objects.

Automobile manufacturers, suppliers, dealers, and service providers understand that quantum computing will eventually have a major impact on most every aspect of the industry. Daimler, Honda, Hyundai, Ford, BMW, Volkswagen, and Toyota all have some form of quantum evaluation program in place.

Classic computers cannot solve many of the significant real-world problems because of computational complexity or because calculations would take an inordinate amount of time, perhaps hundreds, thousands, or even millions of years. Quantum computing offers the potential to solve these problems in a reasonable amount of time. Although current hardware isnt advanced enough to support the number of qubits needed, we are already working to implement error correction solutions in order to build fault-tolerant quantum machines.

The same hardware and error correction constraints limit the full potential of quantum machine learning. In some instances, it has proven to be helpful with current quantum computers; it can also exceed the results of some classical models.

IonQ has a research history with quantum machine learning, so I was looking forward to talking to Peter Chapman, CEO of IonQ, about his partnership with Hyundai Motors.

First, Chapman explained that the partnerships goal is to determine quantum computings potential to provide improved mobility solutions for autonomous vehicles. For these projects, IonQ will use Aria, its latest trapped-ion quantum computer.

IonQ combined its quantum computing expertise with Hyundai's lithium battery knowledge two months ago. It is developing sophisticated quantum chemistry simulations to study battery charge and discharge cycles, capacity, durability, and safety.

As an evolution of their relationship, the IonQ and Hyundai team will develop quantum machine learning (QML) models to detect and recognize traffic signs and identify 3D objects such as pedestrians and cyclists.

Recognizing traffic signs and identifying 3D objects are critical elements of Advanced Driver-Assistance Systems (ADAS) used by autonomous vehicles. ADAS depends upon cameras, lidar, radar, and other sensors for inputs to onboard AV computers that interpret and respond to the driving environment. A 2016 study by the National Highway Transportation Safety Administration found that 94% to 96% of accidents are caused by human error. With quantum enhanced inputs for ADAS, it is likely that human error can be minimized to reduce accidents.

Early in his career, Chapman served as president of a Ray Kurzweil company, where he gained machine learning experience. As a result, he has a deep knowledge of classical machine learning models and the complicated steps needed to identify images. More importantly, he understands why QML will be much faster and more efficient than its classical counterpart.

QML doesn't need numerous processing steps for traffic road sign recognition like classical approaches to object detection, he said. Quantum recognizes a sign and interprets its meaning in one single step.

IonQ has already completed the difficult computational part of the road sign recognition project. It has already trained quantum machine learning models (QML) using a standardized 50,000 image database to recognize 43 different classifications of road signs. Next, IonQ will test its QML model under real-world driving conditions using Hyundai's test environment.

Chapman also explained why he believes quantum machine learning and object recognition will prove much more powerful than classical.

"What happens if your car sees something that it has never been trained on before? Let's take an outlier case, such as a person with a triple-wide stroller, walking two dogs on a leash, talking on their iPhone, and carrying a bag of groceries. If the training data had never seen this scenario, how would the car respond? I think quantum machine learning will fill in those gaps and provide a known response for things it hasn't seen before."

IonQ Quantum Machine Learning milestones

The following summarizes various QML projects IonQ has participated in over the past few years.

December 2020

September 2021

November 2021

Analyst notes:

1. In October 2021, IonQ became the first pure-play quantum company listed on the New York Stock Exchange.

2. While quantum computing is still in its infancy, it's too early to select a technology that will lead to error-free quantum systems that use millions of qubits to solve world-changing problems. The technology that ultimately performs at that level may not even be in use today. Scaling to millions of logical qubits is still many years away for all gate-based quantum computers.

3. Quantum qubits are fragile and susceptible to errors caused by interaction with the environment. Error correction is a subject of serious research by almost every quantum company. It will not be possible to scale quantum computers to large numbers of qubits until a workable error correction technique is developed. I expect significant progress in 2022.

4. Technical details of the IonQ-FCAT daily stock return study are available here.

5. Technical details of the IonQ-Zapata hybrid QML research are available here.

6. Access to IonQ quantum systems is available through the cloud on Amazon Braket, Microsoft Azure, and Google Cloud and through direct API access.

Follow Paul Smith-Goodson on Twitter for current information and insights on quantum and AI

Disclosure: My firm, Moor Insights & Strategy, like all research and analyst firms, provides or has provided research, analysis, advising, and/or consulting to many high-tech companies in the industry. I do not hold any equity positions with any companies cited in this column.

Find more from Moor Insights & Strategy on its website, Twitter, LinkedIn, Facebook, Google+, and YouTube.

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IonQ And Hyundai Steer Its Partnership Toward Quantum Machine Learning To Recognize Traffic Signs And 3D Objects - Forbes

VelocityEHS

Addressing musculoskeletal disorders and aligning risk reduction programs to ESG and sustainability efforts top the agenda.

CHICAGO, April 29, 2022 (GLOBE NEWSWIRE) -- VelocityEHS, the global leader in cloud-based environmental, health, safety (EHS) and environmental, social, and corporate governance (ESG) software, announced today it will host a new virtual event The VelocityEHS Ergonomics Conference on May 3, 2022. During this free, one day conference, experts will provide thought leadership on ways to focus on the job improvement process while reducing workplace injuries related to musculoskeletal disorders (MSDs). VelocityEHS expert speakers include board-certified professional ergonomists (CPEs), certified safety professionals (CSPs), certified industrial hygienists (CIHs), a PhD in machine learning, and a doctor in physical therapy.

Additional topics include implementation of best practices, tools for calculating a return on investment, machine learning advancements, physical demands analysis, the impacts of ergonomics on corporations, and insights from experts on the front lines at Cummins, Lear Corporation, Southwire Company and W.L. Gore & Associates.

Register now for the whole conference or to attend specific sessions. Registrants will also have on-demand access to the sessions for 30 days following the live event.

One of the best ways to judge the health, sustainability and vitality of a global enterprise is to look at how seriously they take ergonomics, said John Damgaard, CEO of VelocityEHS. One thing the very best companies in manufacturing, pharmaceuticals, food & beverage, chemical and so on, have in common is the investment they make in ergonomics and designing risk out of their processes. With more CPEs than any other company, and game-changing technology that harnesses AI & machine learning to help non experts achieve expert results, VelocityEHS is the most trusted ergonomics partner of the Fortune 500 and beyond.

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The free, daylong event features a packed and unparalleled line up of experts and content, with ergonomics insights on a broad-range of topics, including:

Advancing Your Ergonomics Progress10-10:15 a.m. ETPresented by Jamie Mallon, CPE, and Chief Revenue Officer at VelocityEHS. Mallon will share his 25+ years of experience consulting with Fortune 500 companies to help them advance the impact of their ergonomics improvement process, enabling them to identify and design out risk before injury.

Building an Effective Ergonomics Process10:1511 a.m. ETPresented by Kristi Hames, CIH, CSP, Senior Solutions Strategist, VelocityEHS and Christy Lotz, CPE, Director of Ergonomics, VelocityEHS. This workshop covers the key elements of a written ergonomics plan, considerations for establishing your ergonomics team, activities you can perform to enhance stakeholder alignment, and how to select metrics that are aligned with your process maturity and stakeholder objectives.

Process Management and ROI11:1512 p.m. ETPresented by Rick Barker, CPE, CSP, Principal Solutions Strategist, VelocityEHS and Rachel Zoky, CPE, Senior Consultant, VelocityEHS. This session covers ways to sustain a successful ergonomics process by updating your program as it matures.

Quantifying Overall MSD Risk Level: A Panel Discussion with VelocityEHS Customers 12:1512:45 p.m. ETPresented by Blake McGowan, CPE, Director of Ergonomics Research, VelocityEHS; Kevin Perdeaux, CPE, Director of Global Ergonomics, Lear Corporation; and Ryan Goad, CPE, Environmental, Health & Safety Manager, Southwire Company.

A Road Map to ActiveEHS (Customers Only)1-1:30 p.m. ETPresented by Ben Taft, Senior Product Manager, VelocityEHS, this session will explore how ActiveEHS in ergonomics harnesses AI & machine learning along with deep domain expertise from VelocityEHS experts to drive a continuous improvement cycle prediction, intervention and outcomes.

Physical Demands Analysis: The 5 Most Commonly Asked Questions1:45-2:15 p.m. ETPresented by Arielle West, PT, PDT, Solutions Strategist, VelocityEHS, will explore how Physical Demands Analysis (PDA), another tool to manage musculoskeletal disorders is used to match people to job demands.

How Ergonomics and MSD Risk Reduction Efforts Impact Corporate Sustainability Metrics2:30-3:15 p.m. ETPresented by Blake McGowan, CPE, Director of Ergonomics, VelocityEHS, this session will center on the relationship between ergonomics and risk reduction and the necessity for business to up their performance on the ESG and sustainability front.

How Machine Learning is Advancing Ergonomics Effectiveness3:30-4:15 p.m. ETPresented by Dr. Julia Penfield, Ph.D., Principal Machine Learning Scientist, VelocityEHS and Rick Barker, CPE, CSP, Principal Solutions Strategist, VelocityEHS, this session will provide a great understanding of what machine learning is and how it is already being applied to save time and increase the effectiveness in three different EHS use cases.

Determining the Value of New Technology: A Panel Discussion with VelocityEHS Customers 4:30-5 p.m. ETPresented by Blake McGowan, CPE, Director of Ergonomics Research, VelocityEHS; Sarah Grawe, Ergonomics Manager, Cummins; and Michael Mauro, Divisional Ergonomics and Error Proofing Process Owner, W.L. Gore & Associates. This session features a conversation with Cummins and W.L. Gore & Associates on ways to assess the value of new technology.

VelocityEHS virtual events offer attainable learning opportunities to individuals seeking unique perspectives on the common EHS and ESG issues most affecting companies today. Stay up-to-date with current and upcoming conferences, webinars and other learning opportunities by visiting the Webinars & Recordings page and following VelocityEHS on LinkedIn.

The VelocityEHS Industrial Ergonomics solution, now with Active Causes & Controls, is available via the VelocityEHS Accelerate Platform, which delivers best-in-class performance in the areas of health, safety, risk, ESG and operational excellence. Backed by the largest global software community of EHS experts and thought leaders, the software drives expert processes so that every team member can produce outstanding results. For more information about VelocityEHS and its complete award-winning software solutions, visit http://www.EHS.com.

About VelocityEHSRelied on by more than 10 million users worldwide, VelocityEHS is the global leader in true SaaS enterprise EHS technology. Through the VelocityEHS Accelerate Platform, the company helps global enterprises drive operational excellence by delivering best-in-class capabilities for health, safety, environmental compliance, training, operational risk, and environmental, social, and corporate governance (ESG). The VelocityEHS team includes unparalleled industry expertise, with more certified experts in health, safety, industrial hygiene, ergonomics, sustainability, the environment, AI, and machine learning than any EHS software provider. Recognized by the EHS industrys top independent analysts as a Leader in the Verdantix 2021 Green Quadrant AnalysisVelocityEHS is committed to industry thought leadership and to accelerating the pace of innovation through its software solutions and vision.

VelocityEHS is headquartered in Chicago, Illinois, with locations in Ann Arbor, Michigan; Tampa, Florida; Oakville, Ontario; London, England; Perth, Western Australia; and Cork, Ireland. For more information, visit http://www.EHS.com.

Media ContactBrad Harbaugh312.881.2855bharbaugh@ehs.com

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VelocityEHS Dream Team of Board-Certified Ergonomists and AI & Machine Learning Scientists Headline Virtual Ergonomics Conference on May 3 - Yahoo...

InvestorsObserver gives Link Machine Learning a strong long-term technical score of 94 from its research. The proprietary scoring system take into account the historical trading patterns from recent months to a year of the token's support and resistance levels, in addition to where it is relative to long-term averages. The analysis helps to determine whether it's a strong buy-and-hold investment opportunity currently for traders.LML at this time has a superior long-term technical analysis score than 94% of crytpos in circulation. The Long-Term Rank will be most relevant to buy-and-hold type investors who are looking for strong steady growth when allocating their assets. Combining a high long and short-term technical score will also help portfolio managers discover tokens that have bottomed out.

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Is Link Machine Learning (LML) Heading the Right Direction Monday? - InvestorsObserver

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Managing data has always been a challenge for businesses. With new sources and higher volumes of data coming in all the time, its more important than ever to have the right tools in place. Predictive analytics tools and software are the best way to accomplish this task. Data scientists and business leaders must be able to organize data and clean it to get the process started. The next step is analyzing it and sharing the results with colleagues.

Whether you need to up your existing analysis system or establish this capability, take a look at thes round up of predictive analysis tools. Youll find tools and software for both people who are experts at working with data and people who are not.

Contents:

The Alteryx Analytic Process Automation Platform specializes in no-code and low-code analytics building blocks to design repeatable workflows. The platform is designed for companies that want to provide self-service analytics and data science for all departments. Alteryx also uses augmented machine learning to help citizen data workers build predictive models. The companys cloud platform makes it easy to share workflows online, at the desktop and in on-prem data centers and offers built-in integrations with modern cloud ecosystem applications. The Analytic Process Automation Platform puts analytics, data science and process automation in one place by combining data quality and preparation, analytics, data science and automated machine learning and deployment and monitoring into one service. The automation service includes more than 80 natively integrated data sources. Alteryxs Designer service makes it easy to combine data sets, use code-free and code-friendly tools and produce visual workflows and reports.

Alteryx also provides training and educational information about machine learning on its Data Science Portal.Alteryx offers a free 30-day license for Designer for business users. For students, educators and career changes, the company offers a free one-year renewable Designer license. Contact the company for detailed pricing information.

Microsofts cloud platform offers business analytics services for the entire machine learning process. This includes preparing data, building and training models, validating and deploying them and managing and monitoring them. According to Microsoft, the platform can increase the ROI of machine learning products, reduce the steps required to train models by 70% and reduce by 90% the amount of lines of code for pipeline. Azure Machine Learning also offers PyTorch Enterprise, a support program for the open-source deep learning framework that allows service providers to develop and offer tailored enterprise-grade support to customers.

Azure ML also offers responsible AI capabilities to make models more transparent and reliable. Features include visualizations, what-if analysis and model explanation graphs. The platform includes algorithms to test models for fairness and an error analysis toolkit to debug errors and improve accuracy.

Microsoft offers 60 compliance certifications as well as beginner and advanced tutorials. There is a free trial for Azure. There is no additional cost to use Azure Machine Learning but users pay for compute as well as other Azure services including Azure Blob Storage, Azure Key Vault, Azure Container Registry and Azure Application Insights. Pricing options can be customized by type of service, region, currency and time frame.

The Lakehouse Platform combines the functionality of a data warehouse and a data lake. Databricks Lakehouse unifies data warehousing and AI use cases on one platform and provides a single data platform across cloud deployments. The warehouse is built on the open source technology Delta Lake which forms the structured transactional layer. According to the company, this open format storage layer delivers reliability, security and performance for both streaming and batch operations and can replace data silos with a single home for structured, semi-structured and unstructured data. Delta Engine is the high performance query engine. The has SQL and performance capabilities, including indexing, caching and MPP processing. The platform also allows direct file access and direct native support for Python, data science and AI frameworks. Cloud partners include AWS, Azure and Google Cloud.The Databricks Data Science Workspace is a notebook environment that can be used by everyone on the team. Existing notebooks can be imported into a companys Databricks environment or the free community edition.

Databricks has an academy with numerous role-based learning paths, self-paced learning and instructor-led training. The company also offers speciality badges and certifications for data analysts, data engineers and machine learning scientists. Databricks offers a free trial as well as pay as you go and committed-use discounts options. Contact the company for pricing information.

DataRobots AI Cloud Platform supports collaboration for all users from data science and analytics experts to IT and DevOps teams to executives and information workers. The platform includes data engineering, machine learning, MLOps, decision intelligence and trusted AI services. To support decision intelligence, the service has a no-code app builder, AI apps and Decision Flows which create rules to automate decisions. The no-code app builder allows users to turn a model into an AI application without any additional coding. This makes it easier for business users to make AI-driven decisions, according to the company. The apps also include detailed prediction explanations to help users explain any decision made by a model. Users also can use the no-code app builder to perform what-if analysis by changing one or more inputs to create new scenarios and then compare the two results. This transparency allows companies to incorporate feedback from end users and other stakeholders into model revisions.

The company also provides modules for grading existing AI models, setting up policies, rules and controls for production deployments and for generating compliance reports. DataRobot offers options to deploy AI services on any cloud platform, on premise or at the edge.

DataRobot offers a free trial. Contact the company for detailed pricing information.

H2O.ais automated machine learning capabilities make it easier to use artificial intelligence with high levels of speed, accuracy and transparency, according to the company. The companys platform has options for building models and applications as well as monitoring performance and adapting to changing conditions. The services are designed for various roles within a business, including data scientists, developers, machine learning engineers, DevOps and IT professionals and business users.Services in the platform include data visualization, pre-processing transformers, dataset splitting, outlier detection, feature encoding, per-feature controls and automated validation and cross validation.Automated machine learning services include:

The platform also includes a low-code application development framework (Python/R) for user interface creation and machine learning integration.Services for machine learning operations include a model repository, model deployment and model monitoring.

The company offers fully managed cloud services and hybrid cloud services. H2O.ai offers a free trial of the platform.

IBMs Statistical Package for the Social Sciences is used for complex statistical data analysis via a library of machine learning algorithms, text analysis, and open source extensibility designed for integration with big data and easy deployment into applications. The package includes a statistics component for ad hoc analysis, a modeler with algorithms and models ready for immediate use and a modeler in cloud pak for data, and a containerized data and AI service for building and running predictive models in the cloud or on premises. Several related products support predictive analytics software for students, teachers and researchers as well as an analytic server to make predictive analytics easier.

Business analysts can use features in the statistics component to:

IBM recently launched an early access program for beginner and intermediate users to help those groups get started with statistics. The learning modules feature a simplified UI, a guided walk through of the software and a data overview dashboard. This service is in beta and is offered free for 60 days. IBM offers a subscription plan and on-premise licensing editions of SPSS. There are four levels of service: base, standard, professional and premium. Contact IBM for pricing.

This is IBMs platform for data science, formerly known as Data Science Experience. The platform includes a workspace and collaboration and open-source tools for data science. Watson Studio is a core offering in Cloud Pak for Data as a Service. The service includes tools to analyze and visualize data, to clean and shape it and to build machine learning models.The architecture of Watson Studio is built around a project that includes collaborators, assets and tools. Software provided in the studio include:

Projects integrate with Watson Knowledge Catalog services and Deployment spaces provided by Watson Machine Learning services.

IBM offers a free trial of IBM Watson Studio on Cloud Pak for Data. Contact IBM for pricing of multiple licensing options for IBM Cloud Pak for Data, pay-as-you-go pricing for IBM Cloud Pak for Data as a Service and for IBM Cloud Pak for Data System.

This data science software platform provides an integrated environment for data preparation, machine learning, deep learning, text mining and predictive analytics. It is used for business applications as well as for research, education, training, rapid prototyping and application development. According to the company, the platform is robust enough for data scientists while also being user friendly enough for users in the rest of the company. Features designed for data scientists include:

Features for business users include:

The RapidMiner AI Cloud service is built for all users with an augmented and guided experience, a visual UI with a minimal learning curve and an explanation of the data and the modeling process.

The company has a RapidMiner Academy and training and certification services. There are also certified global partners for additional support as well as integrations to speed data access and deployment of machine learning models. Contact the company for enterprise pricing information.

Tableau is an end-to-end data and analytics platform that includes security, governance and compliance along with APIs. Tableau creates trust and confidence by establishing controls, rules and repeatable processes across integration, access and oversight, according to the company. Individual components of the platform include services for data prep, CRM analytics, server management and embedded analytics.Tableau also promises to help customers build a data culture by promoting these values:

Tableau Blueprint is a methodology for building capabilities required for a data-driven organization that covers strategy, agility and proficiency.Companies can deploy Tableau via software-as-a-service, Salesforce Hyperforce, public cloud server and containers and on-premises servers. Tableau Creator is $70/user/month billed annually, Explorer is $42/user/month billed annually and Viewer is $15/user/month billed annually. These services are fully hosted by Tableau. For deployments with Tableau server on-premises or in the public cloud, the prices are $70/user/month billed annually for Creator, $35/user/month billed annually for Explorer and $12/user/month billed annually for Viewer. For individuals, access to Tableau Creator is $70/user/month billed annually.

Sisenses Fusion Platform integrates customized analytics into applications and products to make analytics intuitive and user-friendly, according to the company. The platform has three components for data analysis: Embed, Infusion Apps and Analytics. Embed is an API-first platform that customers can use to build white-labeled analytics into applications and workflows.Customers can use Infusion Apps to ask questions with natural language queries and conduct analysis in Slack, Google Slides, Microsoft Teams and Salesforce. Analytics has code-first, low-code and no-code options for analyzing and visualizing large volumes of data as well as self-service dashboards and apps. The service also has built-in, code-first statistical and predictive analysis libraries and ML technologies.Sisenses Data Connectors integrations cover dozens of other platforms including Airtable, Amazon Redshift, Salesforce Desk.com and Double Click. The companys marketplace includes add-ons, integrations, data pipelines and infusion apps.The Sisense Cloud analytics platform provides scalability and agility to analytics operations and encourages collaboration.

Sisense offers a free trial. Contact the company for pricing information.

Predictive analysis covers statistical techniques for studying data. This includes data mining, predictive modeling and machine learning as methods of making predictions about future events. Predictive analytics has the potential to:

Business leaders can use predictive analytics to increase the chances of success for many initiatives or to test a variety of scenarios quickly.

These tools range from no-code tools to data lakes to machine learning algorithms. Businesses can pick a solution that fits the needs and expertise of each department. Some platforms are complete workspaces and others integrate with existing tools. There are options for cloud deployments and on-prem solutions.

Gartner recommends that companies follow these best practices when selecting predictive analysis tools:

Predictive analytics platforms look at historical data and try to spot patterns. The process relies on data such as customer purchases, weather information or banking habits, statistics such as regression analysis, and assumptions that the future will follow trends from the past.Some types of predictive analytics software use machine learning to revise algorithms based on learnings from the data collected.Data experts and business department leaders can use predictive analytics to test new theories and products before committing to these decisions in the marketplace.

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Best Predictive Analytics Tools and Software 2022 - TechRepublic

During the early days of quarantine and lockdowns, we flocked to TikTok for much needed laughs, distraction, and even recipe inspiration. And were not the only ones. Quarantine has turned me into Betty Mother-F*cker Crocker, so welcome to my cooking show, Lizzo captioned on May 15. The singer, rapper, songwriter, and classically trained flutist can now add vegan recipe developer to her repertoire at the rate shes been posting on TikTok. She first grabbed our attention with her spicy veganized version of the classic McDonalds McChicken Sandwich, and weve been drooling over her recipe videos ever since. From simple frank and beans to vegan ice cream bread, she makes vegan cuisine accessible, fun, and utterly delicious. Were pitching this to the Food Network, because if anyone can make vegan food mainstream, Lizzo can.

Hot Cheetos have amassed a cult-like following, but for vegans in the US, these crunchy spice-covered chips are off limits as theyre ladden with dairy. And while Lizzo feels our pain (she initally stopped eating them to help with her acid reflux), shes developed a hack to satisfying our cravings. The Grammy-winner combines Japense yam potatoes with high-protein tofu, onion, garlic, nutritonal yeast, Kellys Gourmet Cheezy Parm, salt, pepper, habanero hot sauce, and Follow Your Hearts smoked gouda to create a thick and creamy cheese sauce. Pour over a bowl of Takis and kiss Chester the Cheetah goodbye.Watch the video here

You know someone has true talent when they can bust out a catchy tune with a strong beat about vegan frank and beans. Warning: watch this video once, and the song will be stuck in your head for the rest of the day. Lizzo whips up a pot of frank and beans by bringing two cans of baked beans and chopped red onion to a simmer over the stove. She then adds sliced vegan hot dogs and chopped vegan bacon. The video includes a full meal of a homemade iced grapefruit drink and a mixed greens strawberry salad. We know what were making for lunch tomorrow!Watch the video here

Thank you, Lizzo, for introducing us to ice cream bread. How did we not know this existed? We looked up recipes and its literally two ingredientsvegan ice cream and self-rising flour. For this miraculous creation, she used Ben & Jerrys Non-Dairy Netflix & Chilld. The caption demurely stated that her bake was good, but shes using the leftover for French toast. We love how Lizzos mind works.Watch the video here

Three days after the murder of George Floyd, Lizzo posted this video stating, Hey, so Im eating my feelings because the world continues to let me down. The comforting meal consisted of cheesy jalapeo vegan sausage biscuits, homemade fried oyster mushrooms, and a strawberry salad. Shes fairly detailed in this video, so make sure to take notes to recreate this at home.Watch the video here

This artists kitchen is well-stocked! The video guides followers as Lizzo picks bib lettuce from her urban gardening tower and walks inside to find two baskets overflowing with sweet potatoes and bananas. In the next shot, shes sprinkling seeds over avocado toast piled high with fresh chives. To conclude, she zooms over a bowl of bright berries and pours herself a glass of crisp sparkling water. If anything, the soothing ASMR experience is worth the watch.Watch the video here

This recipe is a little complex in that its doesnt follow Lizzos typical minimal-ingredient videos. There are a lot of vegan products on her countertop, but that must be what makes these spicy patties so good. The tender savory pastries are stuffed with seasoned vegan meat, avocado sauce, and fresh cilantro from her garden. Even with the multiple steps, Lizzo makes cooking look so easy.Watch the video here

Lizzo may have created something better than mac and cheese with this toss-together recipe. The star whipped up an herby avocado cream sauce and used it to coat nooch-sprinkled chickpea pasta shells. Served with a side salad of lettuce topped with lime-marinated tomatoes, this is definitely our new favorite way to eat our greens.Watch the video here

For more about Lizzo, read:Lizzo Launches Inclusive ShapewearLizzo Slays Her Cravings for Hot Cheetos With a Clever HackLizzo Promises TikTok Fans Fresh Vegan Cooking Content

Tanya Flink is a Digital Editor at VegNews as well as a writer and runner living in Orange County, CA.

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7 Reasons Why Lizzo Needs Her Own Vegan Cooking Show - VegNews

This month, vegan eggs hit the menu at all 14 residential dining halls at Ivy League university Yale. Made by vegan company Zero Egg, the plant-based eggs are being served five to seven times per week during breakfast and brunch as part of scrambles, in breakfast sandwiches made with Zero Egg patties and Beyond Meats sausage, and as a base for the Vegan Herbed Frittata.

Founded in 2018 in Israel, Zero Egg began making its foodservice debut in the US in 2020 as a versatile replacement for animal-derived eggs. The brand chose to focus on college campuses because the biggest trends in food and beverage tend to emerge there. Generation Z is also a demographic that is acutely aware of the role animal agriculture plays in the climate crisis and is looking to consume more environmentally friendly foods.

Zero Egg

Student diners represent the next 10 to 15 years of restaurant goers, so it was a natural conclusion for us to start on campuses in New England, Graeham Henderson, Zero Egg sales lead for the region, told VegNews. Since Zero Egg has the same taste, texture, and versatility of an ordinary egg, it doesnt just appeal to vegan students either. The majority of studentsupwards of 60 percentwho are ordering our plant-based eggs are non-vegan and would otherwise be consuming ordinary eggs.

In addition to Yale, Zero Egg is available at other college campuses in the New England area, including Colleges of the Fenway, Boston University, Connecticut College, and Mount Holyoke College, with more to come in the fall semester.

Zero Egg

Approximately 1.3 trillion eggs are consumed globally every year and to produce this volume, egg-laying hens are forced to live miserable lives within the industrial animal agriculture industry. In addition to being a more ethical choice, plant-based egg alternatives do not rely on animal biology which presents myriad environmental, individual health, and public health benefits.

A shift toward plant-based eggs means a move away from the overuse of antibiotics, risk of zoonotic disease, and unreliable egg supply chains. Zero Egg was co-founded by food scientist Liron Nimrodi with this in mind. Animal-based foods are just not healthy for you and are hurting the environment and farmed animals, Nimrodi told VegNews. Eggs are part of that, and we at Zero Egg want to be part of the solution for a better tomorrow.

To provide a fully functional substitute, Zero Egg is available to foodservice operators in several formats including frozen liquid, ready-to-eat patty, and shelf-stable powder made from two patent-pending formulations that mimic animal eggs using a blend of plant-based components. Our product functions like an ordinary egg but is entirely made from plants, Nimrodi said. Created with a proprietary blend of plant proteins, Zero Egg has significantly less impact on the environment compared to ordinary eggs, not to mention our product doesnt harm any animals.

Zero Egg

In the US, the leader in the vegan egg category is JUST Egg, a mung bean-based replacer produced by California company Eat Just. Since its debut in 2019, JUST Eggwhich takes far fewer resources to produce than its animal-derived counterparthas sold the vegan equivalent of 250 million chicken eggs and recently gained approval to expand to the EU where it will continue to disrupt the unsustainable chicken egg industry. To date, Eat Just has also saved 43.6 million kilograms of CO2 emissions, 9.1 billion gallons of water, and 13,446 acres of land with its mung bean-based egg alternative.

New entrants in this category can help move the needle toward replacing eggs with plant-based alternatives that are much kinder to the planet. It takes more than 630 gallons of water to produce one dozen chicken eggs. However, Zero Egg cuts that water usage down by 93 percent for an equivalent amount of its vegan eggs. It also uses 92-percent less land, 93-percent less energy, and emits 59-percent fewer greenhouse gasses when compared to traditional chicken eggs. Think about the impact Zero Egg will have on the planet and on the climate crisis if we replace 10 percent of the one trillion eggs that are produced every yearthis is why we wake up in the morning, Nimrodi said.

Zero Egg

In addition to college campuses, Zero Egg is expanding to other foodservice providers in the New England region and beyond. The vegan egg is now served at Crackd Kitchen & Coffee locations, where it is being used in the Southwest Veggurito and can be ordered as a replacement to eggs in any of the chains current dishes. Additionally, Zero Egg is available at Revival Cafe + Kitchen locations in its vegan breakfast sandwiches for a limited time and will be expanding to the permanent menu starting next month. Revival also provides catering services and offers Zero Egg to a number of high-profile corporate tech offices.

For more about vegan eggs, read:This Vegan Egg Cooks, Tastes, and Cracks Like a Chicken Egg German Startup Develops Vegan Egg From Fava BeansThe Ultimate Guide to Egg, Milk, and Butter Substitutes

Anna Starostinetskaya is the Senior News Editor at VegNews and is always keeping an eye on all things vegan in her home city of San Francisco, CA and everywhere else.

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How Vegan Eggs Took Over All the Breakfast Menus at Yale - VegNews

Talk about being a picky eater.

A recent study polling 7,400 vegans and vegetarians from around the world found that more than half of vegans (52%) and four in 10 vegetarians (39%) wouldnt consider a relationship with a meat-eater.

In addition, roughly one in eight vegans (12%) wouldnt even consider dating a vegetarian.

The study was conducted by Veggly, a popular global vegan and vegetarian dating app presumably filled with more peach and eggplant emojis than Tinder.

For many vegans, their veganism is a way life, so its understandable they wouldnt want to be with a partner that consumes animals or animal products, Veggly founder Alex Felipelli explained. Many vegans want to be with someone who shares their values and love of animals.

We believethat if the question was Would you prefer to date a vegan? the result would be close to 100%.

That theory seems to bear fruit, as several other vegan and vegetarian dating apps have also sprung up including Green Singles, Veggie Date and Veggie Connection to cater to the many dining preferences of their users.

Vegetarian diets eliminate meat from a persons plate, while a vegan diet excludes any animal products, including eggs, butter and cheese. A vegan lifestyle can go even further by avoiding all forms of exploitation of, and cruelty to animals for food, clothing or any other purpose, according to The Vegan Society.

As the number of people who change their orders from meat-lovers to veggie-lovers grows The Economist claimed veganism was surging back in 2020 so does the number of people looking for someone to share their salad and ethics.

And all of that has the potential to shift ones dating status from In a relationship to Its complicated.

It can be hard for a lot of vegans to have a serious relationship with a meat-eater, Felipelli told the Wall Street Journal last year. It isnt just about food, its about lifestyle.

Limiting your dating pool to only consider fellow vegan or vegetarians may seem as restrictive as the diets, but experts also agree that it could be beneficial.

Judith Gottesman a matchmaker, dating coach and author encourages singles to join dating apps with more focus.

She told The Post that she always advises people to look for similar lifestyles, values, goals and interests when searching for a match.

They really matter most in being compatible, Gottesman said of creating a more fruitful experience. It makes sense: If youre a dedicated and ethical vegan, you probably dont want to spend your life with someone chowing down on animals.

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Majority of vegans will not even consider dating a meat-eater - New York Post

According to Vegan Fashion Week, clothing is considered vegan if it doesn't feature any animal parts, such as real fur or leather. We know what you're thinking: How can you resist buying a glamorous, statement-making fur coat for elegant winter events or an edgy black bomber jacket to wear every day in the fall? Luckily for you, many brands have started selling faux fur and fake leather, feathers that aren't actually from animals, and silky-looking fabrics that were made without harming animals. By investing in vegan clothing, you'll be protecting wildlife while still looking fabulous.

If you're thinking about buying some vegan clothing but don't know where to start, Animal Outlook rounded up some of their favorite companies that sell vegan apparel. Some of these animal-friendly companies include Herbivore, The Dharma Store, Plant Faced Clothing, and even Moo Shoes if you're looking for vegan footwear options. So, which animal-loving company are you going to check out first?

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What Does It Mean When Clothing Is Vegan? - The List

First came beefy, bleeding vegan burgers. Next, plant-based chicken swooped in as competitors raced to deliver their vegan alternatives to the masses. And now, vegan seafood has entered the chat. From smoked salmon to crispy crab cakes, chewy shrimp, and sushi-grade tuna, the world of vegan seafood is nothing short of a treasure trove. Whether youre already fish-free or seriously contemplating it, here are sixteen vegan seafood products to pile in your cart.

Ocean Hugger Foods

This sushi-grade plant-based seafood company was hit hard by the pandemic. While its raw tomato-based tuna was met with constant praise, the founders decided to temporarily pause production in June 2020 due to the uncertain times. In March of last year, the company announced that it is planning a triumphant return after partnering with a Thailand-based global manufacturer of sustainable foods. Youll have to wait a little longer, but Ocean Hugger products will return to retailers and foodservice businesses. Follow them on Instagram (@oceanhuggerfoods) for the latest updates.Learn more here

Good Catch

From the founders of the popular Wicked Healthy blog and ready-made meal brand, Good Catch has wowed the world with its cooked tuna products. The line of packaged vegan tuna, crabless cakes, and more are available at hundreds of locations across the US and Canada including Whole Foods, Wegmans, Gelsons, and Veggie Grill.Learn more here

New Wave Foods

When replicating animal products, its often the texture that stumps many chefs and innovators. Shrimp was particularly difficult to replicate, until New Wave Foods cracked the code with its algae-based vegan shrimpthe first of its kind. This plant-based shrimp mimics that distinct chew of cooked shrimp perfectly, and the taste is equally on point. The distribution is limited for now, but after closing an $18 million finance round, New Wave is looking to make a splash on restaurant menus.Learn more here

Gardein

Craving something fried? Gardein is a pioneer in the vegan fish sector after gaining a loyal consumer base by sampling its Crabless Cakes at festivals before the pandemic hit. The Fishless Filets and Mini Crabless Cakes are widely available across the US in most major supermarkets and health food stores. Bring on the chips and vegan tartar sauce!Learn more here

All Vegetarian

Not only are these fishy products all vegetarian, but theyre also all vegan, too. This company started out as a wholesale business, selling only to restaurants, but it has since expanded to the retail sector. Look for its perfectly chewy vegan shrimp and shrimp balls at your local vegan grocer or online.Learn more here

BeLeaf

There are a handful of companies making vegan shrimp, but BeLeaf may be the only one mass-producing plant-based ribbon fish (aka salmon steaks). The tender piece of vegan seafood is made with a mix of soybeans, wheat gluten, seaweed, and spices to nail the flaky fish texture and the clean salmon taste. Unlike animal-based salmon, this filet is easy to cook up. Bonus: you dont have to worry about any bones.Learn more here

JINKA

Looking for some major umami to schmear on your bagel? Try JINKAs vegan tuna fish spread. Not quite cream cheese and not quite tuna salad, this smearable, slightly textured tuna works as a dip, spread, filling, and topper. Flavors come in Original, Lemon and Dill, and Spicy. Find it online or at select Bay Area health food stores.Learn more here

Sophies Kitchen

Yes, the vegan seafood is excellent, but were really in love with the tagline: Plant-based seafood thats tasty AF (as fish). This long-standing vegan company makes an assortment of fishy products including breaded shrimp and fish filets, sliced smoked salmon, crab cakes, and canned Toona. If youre looking for plant-based seafood, Sophies is a stellar one-stop-shop.Learn more here

Loma Linda

Whether youre looking for canned or pouched vegan tuna, the Loma Linda brand has you covered. While weve already mentioned a few plant-based tunas on this list, the flavors of this brand are absolute standouts. Tasty varieties include Thai Sweet Chili, Sesame Ginger, Sriracha, Lemon Pepper, and pure Spring Water. Hello, vegan sriracha tuna melt!Learn more here

Cavi-art

Oh, you fancy! Cavi-art has created vegan caviar for the refined and sophisticated palates. These salty umami pearls are made from seaweed, water, salt, spice extracts, and a stabilizer to give them that unique fish egg texturewithout the fish. Like fish eggs, vegan caviar is a rare find in stores, but anyone can purchase a case online at Vegan Essentials. You have to try it at least once!Learn more here

Goldie Lox

Created by a scientist turned chef, this vegan smoked salmon is a must-have for any Sunday brunch spread. These fishless strips are made using organic carrots, dill, salt, and tamari for a smoky flavor perfect for topping on your favorite bagel. Find it in select San Francisco grocers or online.Learn more here

Hungry Planet

Founded to improve human and planetary health, Hungry Planet and its selection of plant-based meats arent to be missed. These chef-crafted alternatives were perfected over a decade-long research and development, and the proof is in the pudding. These crispy, golden crabless cakes are packed with fiber and proetin, and are sure to be a hit with everyone at your kitchen table.Learn more here

Save da Sea Foods

When it comes to seafood staples, this Canada-based brand has you covered. Choose between tuna salad, classic smoked salmon, or smoked salmon with dill and capers. All products are free of gluten and soy, making them allergen friendly too boot.Learn more here

The Plant Based Seafood Co

This women-operated, family-owned company isnt just whipping up vegan fishtheyre wowing us with spice-dusted vegan scallops. Elevate your dinner with a helping of these konjac-based bites (ready in just two minutes!). Dont forget the wine.Learn more here

Vegan Zeastar

Its no surprise this vegan sashimi went viral. These realstic slabs of tuna and salmon sashimi took our collective breath away, and their familiar tastes and textures kept us coming back for more. Dont miss Vegan Zeastars Shrimpz (in Crispy Lemon and Crispy Chili flavors), Kalamariz, and Tasty Cod. Its a vegan seafood extravaganza!Learn more here

Current Foods

Previously known as Kuleana, food technology startup Current Foods is making a splash in the vegan seafood sector. The brands sushi-grade vegan tuna was named one of the best 100 inventions of 2021 by TIME magazine. Free of the top eight allergens, this plant-based tuna is made from a blend of bamboo, potatoes, radish, tomatoes, algae, and peas. The results? Familiar flavors and perfect textures that will make you forget about the real deal.Learn more here

Tanya Flink is a Digital Editor at VegNews as well as a writer and runner living in Orange County, CA.

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16 Vegan Seafood Options That Are Swimming in Flavor - VegNews