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The Most Impactful Issues in Artificial Intelligence Ethics

Aditya Chakurkar | December 27, 2021 | 10 views

The_Most_Impactful

Can smart machines outthink us, or are certain elements of human judgement indispensable in deciding some of the most important things in life?”

Michael Sandel, Political Philosopher

What are Artificial Intelligence Ethics Issues?

It is one of the most frequently asked questions as AI advances. As a result, several potential artificial intelligence ethics issues are of concern for various reasons. Some examples of such ethical issues are:

● How AI could harm people
● How AI could manipulate people
● How AI could erode human autonomy

One of the key concerns around AI is that it has the potential to harm people. For example, AI can create fake news articles that only exist to mislead people. AI can also create propaganda videos or images to influence people's opinions. AI can also create fake social media profiles to scam people.

Unemployment and Wealth Inequality

It's not a secret that hard work has become less common in the past few decades, with many people putting their jobs on the line for this new hot trend called automation. It is more than just a fad. Automation is quickly becoming a dominant force in every industry—a surprisingly fast development that's caught many people, including economists, by surprise. The McKinsey Global Institute estimates that up to 400 million jobs could be automated by 2030.

That’s where artificial intelligence grabs everyone’s attention. With the rapid expansion of AI capabilities, it's clear that robots and algorithms will replace many jobs.


Issues with Machine Ethics & Their Effects on Humanity

With the rise of our new AI overlords, it is essential to remember that machines will always lack the critical features necessary to pose any threat to humanity. That includes empathy, intuition, and common sense.

The emerging stories about how dangerous this technology can be are familiar nowadays. However, these media reports are usually exaggerated for the sake of clicks.

Before long, life without human supervision will be entirely possible. Although this might not seem like our best interest on the surface, it is actually humanity's greatest hope for survival.

The need for humans to work becomes less and less significant while the demand for labor decreases proportionately with the rise of automation.


Problems with Robots

Several ethical issues of robotics can be a concern for various industries. As if the endless onslaught of Hollywood movies about robots going rogue and taking over the world wasn't enough, there are some genuine problems with the development of artificial intelligence.

Chief among these is the possibility that robots can become so advanced that they could outstrip human intelligence. Some experts even fear that AI could eventually become self-aware and decide that humans are no longer necessary.

There are also concerns that robots could replace human workers in a wide range of industries, leading to mass unemployment. So it's not hard to see why some people might view the development of AI with alarm.

However, it's important to remember that these concerns at this stage are still purely hypothetical. The reality is that the development of AI is still in its infancy, and there are many benefits to be gained from it.

I wouldn’t have a central AI group that has a division that does cars, I would have the car people have a division of people who are really good at AI.”

Jason Furman, Professor of the Practice of Economic Policy and a Former Economic Adviser

Example of Ethical Issues around AI


AI in Law

As AI continues to evolve and become more advanced, governments are starting to notice and have begun making laws surrounding its use. It is mainly in response to the potential for AI to be used for malicious purposes, such as cybercrime or mass surveillance.

For example, the European Union has released a document outlining its plans to govern AI. The first objective of the document is to establish a definition of what constitutes AI and how it differs from existing technologies. Their second objective is to develop a legal framework surrounding liability for their actions.

The United States is also taking steps in this direction, as its Federal Trade Commission has released a report recommending that AI-powered devices be subject to the same consumer protection laws as other devices. This is in response to the increasing number of AI-powered devices on the market, such as voice assistants and home robots.

As AI grows in influence and power, we will likely see more governments introduce laws surrounding its use.


AI in Arts

Think AI and the first thing that comes to your mind is probably cutting-edge technology and science fiction-like robots. But what about its use in the arts? Believe it or not, artificial intelligence is becoming an increasingly common tool for artists and art enthusiasts alike.

There are many ways AI is being used in the arts. For example, some artists are using AI to create completely new pieces of art, while others use it to help create and distribute their work. Additionally, AI is being used to analyze and interpret art and to teach people about art history and theory.

However, the use of AI in the arts raises a few questions related to artificial intelligence ethics. For example, how much does the final art rely on human artworks? Who is the real author of a particular artwork? What moral rights does the art reflect? And so on.

Artworks created using AI need new guidelines that offer the proper justice to the work of both the “original” author and the technology/algorithms.


AI in Automobiles

The use of AI in the automobile industry gave birth to autonomous cars—cars that can move without little or no human interference. They come with numerous sensors to analyze the surroundings and proceed accordingly. The independent driving computer system processes tons of data throughout this operation.

Such cars have to undergo strict training to understand the data they collect and make accurate decisions.

Humans can decide morally in various situations. For example, suppose a human is driving a car. He sees a jaywalker in the middle of the road. He morally decides to slam the brakes to stop the vehicle. In this way, he shifts the risk from a jaywalker to people sitting in the car.

Now consider an autonomous vehicle with a faulty braking system moving at 50 mph towards a mother and her 3-year-old. Even a slight deviation can save one of them. However, the car’s program decides who will get hit or who will be saved.

Being a human would be the most challenging call. This is what the ethical issue of AI in automobiles is.


Solution for Artificial Intelligence Ethics Issues

The questions around artificial intelligence ethics issues are complicated. They need innovative solutions, and those can be controversial. Several initiatives are being taken worldwide to minimize the negative impact of AI. For example, the Institute for Ethics in AI in Munich carries out detailed research related to the use of AI in various sectors.

The following are the best solutions to eliminate artificial intelligence ethics issues:


Developing an Artificial Intelligence Ethics Framework

An ethical framework for data and AI usage can be an excellent solution for AI machine ethics and ethical problems with robots. With a properly maintained governance structure, companies can use the framework to set ethical standards. It also suggests how to incorporate all the primary artificial intelligence ethics.


Promoting Awareness on Artificial Intelligence Ethics Issues

The overall culture of an organization will help avoid artificial intelligence ethics issues. Therefore, companies should develop a culture that promotes awareness of AI ethics, machine learning ethics, problems with robots, etc. This will allow the employees to raise doubts about every aspect of the AI system.


Setting Up A Governance Council Within the Organization to Monitor AI Ethics

Companies should set up a dedicated council for identifying risks and issues related to data, cybersecurity, privacy, and fairness in AI use. Such committees should include subject matter experts like ethicists (internally or externally) to carry out the following tasks:

  • Ensure all the regulatory and legal risks are handled well
  • Ensure a stage-by-stage strategy for ethical AI practices.
  • Monitor how employees handle ethical issues related to AI


Frequently Asked Questions


What are the main artificial intelligence ethics issues?

The following are the major artificial intelligence ethics issues that can take a major toll on any organization in terms of growth, revenue, and efficiency:

  • Lack of quality data
  • Reduced physical integrity
  • Increased unemployment
  • Lack of innovation
  • Asymmetry in power
  • Discrimination, nepotism, and unfairness
  • Security issues


What are the main principles of artificial intelligence ethics?

The sole purpose of AI ethics principles should be to promote transparency and fairness within the system. The following are the principles of ethical AI:

  • Explainability and transparency
  • Easy-to-govern
  • accountability
  • safety and data security
  • Reliability
  • Impartiality
  • Social and personal well-being

 

Why are artificial intelligence ethics important?

The ethics of AI systems are crucial for many reasons. First, they offer regulatory and safety guidelines that prevent severe issues for the entire human race. Plus, they are necessary to develop friendly, fair, transparent, unbiased, reliable, accountable, governable, and safe AI systems.

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Article | June 1, 2022

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Augmented Reality: A Dynamic Change to Enhance Your Business

Article | May 5, 2022

Meta Description: Evaluating the impact of augmented reality in business ROI, while also understanding how CMOs leverage AR effectively in their marketing mix. While several technological advancements have been aiding in improving lifestyle, they have also been making drastic impacts on the business front. Over several years now, the world has seen various exposure to augmented reality. The usage of Augmented Reality for business has effectively transformed the technology from an entertainment concept to a crucial enterprise tool. According to Statista, 23 million jobs across the globe could be directly affected by AR and VR by 2030, and over 824,000 of those jobs are currently using these technologies in their workplace. Impact of Augmented Reality on Business In simple terms, Augmented Reality (AR) is a computer-generated enhancement that is placed over the existing reality we see with our human eyes. It offers the option to add dimension, sound and other experiences to any two-dimensional picture or video. Even when this might seem like something complex to be implemented in business, it isn't as challenging as it looks. With each passing year, AR has effectively been penetrating deeper into businesses, making a drastic impact on various functioning. Marketers have effectively been integrating the use of AR into their marketing strategies, and it has grown overall in the mainstream business functioning by being readily available for users to leverage. Industries That Should Leverage Augmented Reality Technology Uses of Augmented Reality is a prospect that business owners across multiple industries leverage to their advantage. While the core idea is to use the technology to aid and improve human performance, the industries that effectively utilize this resource are: Healthcare Education Travel and Tourism Manufacturing Defense Automotive Industry Retail How Seamless Integration of AR Can Impact Your ROI? Facebook said in March 2021 that it had allocated a complete 20% of its personnel to AR and VR development. That is a really massive investment by a corporation that has built a reputation for wisely investing in monetization and focused on creating bottom-line results. Augmented reality is on the path to becoming the next most significant development in an array of industries, ranging from medical to consumer retail. With the nature of augmented reality technology being highly dynamic, it is essential to have a successful strategy that ensures the integration of AR solutions that provide accurate and tangible results that align with the audience. Additionally, uses of augmented reality in business have also been capable of creating more meaningful engagement with customers. For the first time, new forms have made interaction real and measurable. As a result, brands may see precisely how many people engage with their collateral, how many times and where, for how long, and which direct actions they took: purchase, discount coupon, or social shares, for example, by leveraging IR/AR to turbo-charge paid media. "I do think that a significant portion of the population of developed countries, and eventually all countries, will have AR experiences every day, almost like eating three meals a day, it will become that much a part of you." Tim Cook, Chief Executive Officer of Apple Future of Your Business with AR Integration While augmented reality in business is becoming a crucial component for businesses these days and will revolutionize the future of business. According to Global Market Insights, the global market for AR goods will rise by 80% to £165 billion by 2024. The rise of the AR industry is closely tied to increased attention and investments from leading technology firms such as Facebook. Overall, the augmented reality technology market will develop at the fastest rate by 2023, primarily to the growing usage of smartphones, tablets, and other devices in consumer, commercial, and business settings to adopt AR technology. Furthermore, with the rising need for augmented reality in healthcare and retail, there are a plethora of new prospects and rising demand for augmented reality in architecture and the corporate sector. How Are CMOs Leveraging AR for Their Marketing Mix? Several top executives and leading CMOs are leveraging the benefits of augmented reality to expand the engagement, awareness and value around their services and products. In addition, numerous organizations from different industries and of various sizes in the B2C and B2B space are now using augmented reality technology to differentiate their product and services by effectively implementing AR strategies in their marketing mix. With a game-changing armor in their arsenal in the form of augmented reality, marketing executives trying to promote and sell more successfully can hence perform better, with purchasing experience becoming the new focal point. Conclusion Augmented reality in business is a prospect that offers a massive opportunity to engage with millions of users effectively. AR offers executives to ideally establish an immediate and sensory-driven connection of the brand with consumers by forging an emotional interaction. Repetitive engagement is a successful advertising approach for companies since it only requires AR app development expenditures, and additional benefits may be gained via repeated exposure. In the ever-dynamic state of our current existence, leveraging the benefits of augmented reality can come handy in elevating your business to the next level. FAQs How Can Customers and Businesses Benefit from AR? AR effectively increases engagement and interaction and helps provide a richer user experience. Several research has shown that AR increases the value of products and brands. Implementing AR activities is ideal and conveys innovation and responsiveness from forward-thinking brands. How Does AR Help Organizations Gain a Competitive Advantage? Augmented reality allows the organization to create a unique customer experience while also eliminating cognitive overload. It also ensures that user engagement heightens along with competitive differentiation. AR, after all, is a technology that enables a pure blending of physical and digital reality. How Will the Use of AR Technology Impact the Future of Business Functioning? Augmented reality is constantly evolving to become an emerging marketing and sales strategy trend. AR technologies allow organizations to provide their customers a unique experience with convenience by tapping into their smartphone devices.

Read More
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How Does IT Vendor Selection and Management Work?

Article | May 4, 2022

What Is the Importance of IT Vendor Selection and Management? Ideally, the IT vendor management process is an umbrella term for all the processes and systems organizations use to manage their IT suppliers. This is where an organization works with vendors to optimize its supplies and services. There could be several vendors an organization is associated with for unique services and offers. With proper vendor management, an organization can take appropriate measures to control costs, reduce potential risks, and ensure excellent service delivery. But the catch here is that it isn't as easy as it sounds. This includes researching the best available vendor, sourcing and obtaining pricing information, gauging the quality of work, managing relationships, and evaluating performance by setting organizational standards. Most Common Challenges in Vendor Management Even though there are many benefits, organizations face certain challenges during IT vendor selection and their management. Some of these most common challenges are mentioned below: High administrative costs Incomplete documentation Non-compliance Poor vendor relationships Security breaches Supply chain inefficiencies While there were some nuanced changes in the selections between various businesses, both large and small, the results indicate that organizations often face the same challenges no matter where they’re coming from. How Do IT Vendor Selection and Management Help an Organization? In contemporary times, with geographical and economic barriers constantly diminishing, organizations look for different types of vendors worldwide. Even if the organization is working with just one vendor, it is essential to have effective vendor management in place. With proper vendor management, an organization can experience the following benefits: Better Selection With the right vendor, your organization can benefit from a more extensive selection of vendors, resulting in more choices and better costs. Better Contract Management If there is multi-vendor management in place, your organization can benefit from a centralized view of the current status of all contracts and other useful information. This will enable your organization to achieve better decision-making capabilities. Better Performance Management Using a vendor management system, an organization can get an integrated view of the performance of all the vendors. This would give your organization a clear understanding of what is working and what is not. Better Vendor Relationship Managing multiple vendors at the same time can be a difficult task. By accumulating all vendor-related information in a single place, organizations benefit from getting all required information at once, and this can influence your decision-making process. Exploring the Ideal Process of IT Vendor Selection In a world where we are constantly progressing with increasing IT specialization, organizations must be able to rely on their partners. There are some specific steps that an organization can take up to make the whole IT vendor selection process more successful. The six-step process of ideal IT vendor selection: Kick-off and requirement definition Market research and first vendor filtering Request for proposal Evaluating responses Proof of concept Choosing the vendor There are also some common mistakes that organizations make while selecting their vendor. Some of these common errors are listed below: Not evaluating the vendor and only their offerings Communication indiscretion Not comparing vendors or similar stature Today, outsourcing is increasingly used by companies as an enabler for innovation. Technological advancements drive improvements in service delivery, which positively impact cost, enhance functionality, improve service quality, and reduce the importance of location on service delivery. Disruptive technologies like cloud computing enable solutions such as Salesforce.com or ServiceNow to accelerate speed to value and drive business growth. This leads to a change from the traditional IT organization to the next generation IT organization. The operating model needs more agility to respond faster and at different speeds to new service offerings. Outsourcing models have reached their third generation and involve a multi-vendor environment, requiring more transparency and integrated vendor management. Best Techniques to Improve Vendor Management The vendor management process is a crucial component for any organization, as it allows them to build a relationship with their suppliers and service providers that would help strengthen their business. Vendor management is not only about negotiating the price; the most essential aspect is coming to a conclusion that would mutually aid both organizations. Some effective techniques that can be utilized for effective IT vendor management are: Share information and priorities Balance commitment and competition Allow critical vendors to help you strategize Build partnerships that would last long term Try to understand your vendor's business process Negotiate and conclude with a win-win agreement Come together on value Conclusion Ideally speaking, vendor selection and managing that relationship can sometimes be challenging. Once you follow the process mentioned above to select the right vendor for your organization, the steps ahead will get a little easier. However, there is still the process of managing and building that relationship with the vendor. "The objective of vendor management is to fortify company success and overall marketplace performance." - Sean-Michael Callahan, Principal at The NiVACK Group. FAQ What Is Vendor Management in the IT Sector? The process that allows organizations to control costs, strengthen service, and reduce risks throughout the process of outsourcing to vendors while getting the most value from the investment is called vendor management in the IT sector. What Is a Vendor Selection Process? The vendor selection process is a subsidiary stage that allows for the clear stating, defining, and approval of those vendors who are eligible to meet the requirements of the procurement process. What Is the Role of Vendor Management? The vendor management process ideally facilitates and maintains relationships between your organization and vendors, negotiating contracts, creating standards for the vendors, and finding the best available vendors.

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SOFTWARE

How SAAS Is Redefining Software Industry

Article | April 21, 2022

Software-as-a-Service (SAAS) has been a trending topic in the tech field in recent times. The success of the cloud has accelerated the demand for software delivery from on-premises to cloud-based. Start-ups are in a rush for SAAS transformation, delivering the very same solution over the internet. From Google Docs and Sheets to enterprise-level software, SAAS has established a foothold in every sector. With the oncoming of SAAS, the perception of computer software has changed. In this article, we will take a look at how SAAS is redefining and transforming the software industry. Better Accessibility Any software that is preferred to have better and centralized availability is preferred. Better availability is one of the factors that makes SAAS stand out. With centralized availability of both applications and data, users will have a hassle-free experience – with zero installation overheads and no commitments to carry in any device and data. SAAS is accessible from anywhere around the world on any device. There is a big advantage to SAAS over traditional software, which can only be used on a specific device. Ease of Upgrade To ensure continued security and access to new features, software releases are followed by updates and upgrades, which, once issued, become the sole responsibility of the user to install. A hassle-free upgrade makes SAAS the solution to be chosen. All updates and upgrades are performed on the server side, ensuring no downtime and minimal installation troubles. Moreover, most users do not take the updates and upgrades into account due to their delay in installation and trouble setting up. In this aspect, SAAS enables providers to better serve their users by ensuring they are using the latest releases and fixes. Zero Hardware Upgrades As time moves on, software demands higher resources for it to work smoothly. Zero hardware upgrades will bring a new and better user experience. All the hardware configurations will be managed at the cloud level, with no changes required on the client-side. A large increase in resources might have an influence on the subscription cost, but it is a better alternative to requesting end-users larger hardware. This will be a beneficial aspect for resource-heavy applications like graphics and design-related applications. Thus, a major part of configuration at the hardware and software levels (drivers) is abstracted from the users. Better Security and Protection from Piracy Traditional on-premise software is always vulnerable to cracking and piracy. With SAAS tools and software, there will be no piracy, and increasing security can be feasible. SAAS works on a subscription model where the purchase of the software is tied to a user account, and a fee is paid monthly or yearly to use the software. On-premise software is subject to reverse engineering, where the activation system is tampered with, and the software can be used for free. Similarly, data has better security in the cloud with continuous encryption and backup than on an on-premise system, wherein the data security and backup require user effort as well. Zero Compatibility Issues Software programs are subject to compatibility requirements where the OS or certain dependencies might not support a specific piece of software. With SAAS, there are no more compatibility-related conflicts since the OS and other dependencies and resources are managed by the provider itself. End-users need not comply with any compatibility requirements for the software to work. This aspect also provides users an advantage in terms of storage. The application and its dependencies usually take up a large amount of space. SAAS takes care of dependencies on the server end. Better Team Collaboration SAAS is an option that proves better for collaboration-based teams. Software delivery over the network comes with an account linked to it for sign-in and collaboration. Teams that work together can get better benefits when using SAAS tools since they enable sharing and collaboration on work items. Traditional software has limited or no collaboration capabilities, thus limiting productivity. SaaS can also keep data in sync on a number of devices, giving users a real-time experience.

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AI Quality Leader TruEra Receives Investment from Hewlett Packard Enterprise

TruEra | June 23, 2022

Hewlett Packard Enterprise announced today that it has invested in TruEra through its venture capital program, Hewlett Packard Pathfinder. TruEra offers the first suite of AI Quality management solutions for managing model performance, explainability, and societal effect. The $25M Series B round TruEra announced in March 2022 is now extended. Hewlett Packard Pathfinder invests in market-leading start-ups, develops solutions fusing the technology of portfolio companies with Hewlett Packard Enterprise goods, and designs collaborative go-to-market strategies. Hewlett Packard Pathfinder also keeps a careful eye on longer-term disruptive innovation, supporting the development of cutting-edge technology. "We're excited to become an investor and to partner with TruEra in developing comprehensive solutions for our enterprise customers in conjunction with our High-Performance Computing offering," said Paul Glaser, Vice President and Head of Hewlett Packard Pathfinder. The quality challenge, the following significant AI challenge, is addressed by TruEra. In order to quickly correct problems and maintain peak performance, ML teams can use TruEra's solutions to explain, analyze, and test the performance, risk, and responsible AI characteristics of models early in the development process. As a result, numerous Fortune 1000 businesses have chosen TruEra as their preferred provider because of its distinctive, whole lifecycle approach to model quality. "AI model quality and ML Ops have emerged as considerable challenges for enterprises deploying and scaling machine learning models. Solving these challenges is imperative for AI success, and TruEra stands out for its deep expertise, differentiated technology and practical experience helping companies deliver and monitor AI applications." Ali Wasti, Managing Director, Hewlett Packard Pathfinder Top-tier investors such as Menlo Ventures, Greylock Partners, and Wing Venture Capital have contributed approximately $45 MM to TruEra. Anupam Datta and Shayak Sen, co-founders of TruEra, conducted academic research at Carnegie Mellon University that served as the basis for the company's technology. "Hewlett Packard Enterprise is a leading, trusted provider to the enterprise, and is known for its ability to ensure that cutting-edge innovation delivers proven results. We're looking forward to working closely with the HPE team as partners on customer engagements," said Will Uppington, CEO and co-founder, TruEra.

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GENERAL AI

PyTorch Lightning Creator, Lightning AI, Launches Open-Source Platform and Raises $40 Million Series B to Reinvent the Way AI is Built

Lightning AI | June 18, 2022

Lightning AI today unveiled the groundbreaking Lightning AI platform, backed by a $40 million Series B funding round, that completely reimagines how Artificial Intelligence (AI) products, services, and experiences are built. With Lightning AI’s new platform and framework, the company is introducing a frictionless way to build AI-powered products and services as apps composed of modular components that are seamlessly integrated and connected. Serving as the “operating system for AI,” Lightning AI’s platform ushers in a new era of accessibility and sophistication in the field of AI technology. The platform and underlying framework introduce a novel way to build AI by providing a unified experience that accelerates the deployment of AI technology across academic and enterprise use cases. Amid a fragmented machine learning ecosystem, Lightning AI’s suite of extensible open-source components and apps simplifies the underserved space and helps advance the widespread adoption of AI technology. “Launching this platform is a vital step for our company and the industry. “From day one, I wanted to reimagine the experience of building artificial intelligence beyond the current surfeit of tools and systems. Until now, there hasn’t been a way to build production-grade AI apps that takes into account the entire pipeline from development to production. Current options are limiting, highly prescriptive, and lack the flexibility needed to leverage AI in real-world scenarios. Imagine wanting to make a phone call and you’re simply handed the disparate parts that make up a working telephone, hoping that one day you’ll be able to make a phone call. Lightning AI takes the principles that have made PyTorch Lightning one of the fastest-growing open-source projects in history - simplicity, modularity, and sustainability - and applies them to the task of unifying the entire AI development and infrastructure lifecycle.” William Falcon, Lightning AI co-founder and CEO Lightning AI is the culmination of work that began in 2018 at the New York University CILVR Lab (Computational Intelligence, Learning, Vision, and Robotics) and Facebook AI Research. As a Ph.D. student working alongside advisers Kyunghyun Cho and Yann LeCun, William Falcon created and open-sourced the popular PyTorch Lightning framework. The explosive growth of the project within the AI community led Falcon to build a platform and company focused on eliminating barriers to widespread AI adoption. Grounded in the success of the PyTorch Lightning framework, the company built Grid, a platform for developing and training machine learning models on the cloud. The key to the company’s previous successes has been its unique ability to abstract away engineering infrastructure from the machine learning lifecycle while maintaining rigorous flexibility for experts who want full control over what they’re building. The Lightning AI platform and framework are powered by these groundbreaking advancements, enabling users to conceptualize, build, and deploy AI technology in a matter of weeks, compared to the months and years it would normally take. "We are excited about the development Lightning AI is leading by allowing AI-driven applications relevant to specific verticals come to life in a simple way. The partnership will bring further ease-of-use to customers and fit well with AWS’s industry, use-case and business problem driven approach,” said Dr. Kristof Schum, Global Segment Leader of Machine Learning at Amazon Web Services. $40M Series B Fuels Lightning AI Platform and Community Growth This $40 million Series B funding round, led by Coatue with participation from Index, Bain, First Minute Capital, and the Chainsmokers’ Mantis VC, brings the total raised to date to $58.6 million. Coatue General Partner Caryn Marooney has joined the board of directors, which also includes Index Ventures Partner Bryan Offutt. The capital will fuel further technology innovation, fund new AI research, and be invested back in the company’s growing user community and ecosystem. Lightning AI’s mission is to lower the barriers to AI adoption as the global AI market is skyrocketing and on track to exceed $500 billion by 2024. “As more companies across every sector leverage AI for crucial functions, they need a solution that makes it simple to consume, train, and use AI while also building applications free from vendor lock-in and specialized AI experts,” said Caryn Marooney, General Partner, Coatue. “Coatue immediately saw the potential and significance of Lightning AI’s mission to democratize AI. We look forward to supporting William and his team as they write a new playbook for AI deployment.” The Lightning-Fast Way to Build AI Apps Lightning AI allows researchers, data scientists, and software engineers to build, share and iterate on highly scalable, production-ready AI apps using the tools and technologies of their choice, regardless of their expertise. To solve any kind of AI problem from research to deployment and production-ready pipelines, users can simply group components of their choice into a Lightning App and customize the underlying code as needed. Lightning Apps can then be republished back into the community for future use, or kept private in users’ personal libraries. Lightning AI combines a wide variety of extant tools into a modular, intuitive platform for building AI applications in research, enterprise and personal contexts. It is the foundation of the growing Lightning ecosystem, which provides developers with a suite of ready-to-use tools and required infrastructure and compute resources, as well as community support for building AI applications. The Lightning AI platform is available now and includes: The new Lightning framework, which extends PyTorch Lightning’s simple, modular, and flexible design principles to the entire app development process A collection of tools and functionalities relevant to machine learning, including workflow scheduling for distributed computing, infrastructure-as-code, and connecting web UIs A gallery of AI apps, curated by the Lightning team, which can be used instantly or further built upon A library of components that add functionalities to users’ apps, such as extracting data from streaming video A hosting platform for running and maintaining private and public AI apps on the cloud The ability to build and run Lightning Apps on private cloud infrastructure or in an on-prem enterprise environment About Lightning AI Lightning AI is the company reimagining the way AI is built. After creating and releasing PyTorch Lightning in 2019, William Falcon launched Lightning AI to reshape the development of artificial intelligence products for commercial and academic use. Focusing on simplicity, sustainability, modularity, and extensibility, Lightning AI streamlines the lifecycle of machine learning development to expand widespread AI adoption. Its aim is to enable individual and enterprise users to build deployment-ready AI tools without having to hire experts or sink resources into in-house infrastructure.

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H2O.Ai Expands Snowflake Partnership for AI Transformations

H2O.ai | June 16, 2022

H2O.ai showcased a unique set of capabilities and use cases that enable rich insights by seamlessly connecting data and machine learning. Snowflake and H2O.ai bring together platforms for data and machine learning to help more clients develop with AI through a native connection that gives users access to H2O.ai's powerful machine learning capabilities straight from their Snowflake environment. Through several pre-built connections, customers may simply access the machine learning capabilities of H2O.ai from within the Snowflake Data Cloud for near real-time analysis. This shortens learning cycles, decreases processing time dramatically, assures that predictions are based on the most recent data, and makes these predictions accessible to any application built on top of Snowflake. Customers such as Infutor utilized the H2O.ai combination with Snowflake powered by Snowpark and Java User-Defined Functions (UDF) to avoid the need for additional platforms and AI-related expenses. "H2O.ai reduced our AI inference costs on Snowflake by 55X. H2O.ai partnership and support has made the integration that much more seamless and easy to leverage." Gary Walter, CEO of Infutor, a Verisk business H2O.ai is extending its partnership and dedication to Snowflake users in a number of vocations and sectors, including: Financial services Manufacturing Healthcare Tarik Dwiek, Head of Technology Alliances at Snowflake, said, “Our partnership with H2O.ai can help optimize the supply chain across multiple industries including manufacturing, telecom, banking and retail. With H2O AutoML, users have the ability to make, operate, and innovate for their customers and partners to reduce risks, improve customer experiences, drive growth, and improve efficiency.” Sri Ambati, CEO and founder, H2O.ai, said, “H2O AI Cloud is democratizing AI on Snowflake’s Data Cloud helping our customers personalize their offerings and bring efficient flows into their business. The tight-knit multi-cloud integration of H2O AI engines and AI App Stores drives consumption on Snowflake Data Cloud reducing costs for customers and powers organization-wide transformation needed to adapt quickly.”

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AI Quality Leader TruEra Receives Investment from Hewlett Packard Enterprise

TruEra | June 23, 2022

Hewlett Packard Enterprise announced today that it has invested in TruEra through its venture capital program, Hewlett Packard Pathfinder. TruEra offers the first suite of AI Quality management solutions for managing model performance, explainability, and societal effect. The $25M Series B round TruEra announced in March 2022 is now extended. Hewlett Packard Pathfinder invests in market-leading start-ups, develops solutions fusing the technology of portfolio companies with Hewlett Packard Enterprise goods, and designs collaborative go-to-market strategies. Hewlett Packard Pathfinder also keeps a careful eye on longer-term disruptive innovation, supporting the development of cutting-edge technology. "We're excited to become an investor and to partner with TruEra in developing comprehensive solutions for our enterprise customers in conjunction with our High-Performance Computing offering," said Paul Glaser, Vice President and Head of Hewlett Packard Pathfinder. The quality challenge, the following significant AI challenge, is addressed by TruEra. In order to quickly correct problems and maintain peak performance, ML teams can use TruEra's solutions to explain, analyze, and test the performance, risk, and responsible AI characteristics of models early in the development process. As a result, numerous Fortune 1000 businesses have chosen TruEra as their preferred provider because of its distinctive, whole lifecycle approach to model quality. "AI model quality and ML Ops have emerged as considerable challenges for enterprises deploying and scaling machine learning models. Solving these challenges is imperative for AI success, and TruEra stands out for its deep expertise, differentiated technology and practical experience helping companies deliver and monitor AI applications." Ali Wasti, Managing Director, Hewlett Packard Pathfinder Top-tier investors such as Menlo Ventures, Greylock Partners, and Wing Venture Capital have contributed approximately $45 MM to TruEra. Anupam Datta and Shayak Sen, co-founders of TruEra, conducted academic research at Carnegie Mellon University that served as the basis for the company's technology. "Hewlett Packard Enterprise is a leading, trusted provider to the enterprise, and is known for its ability to ensure that cutting-edge innovation delivers proven results. We're looking forward to working closely with the HPE team as partners on customer engagements," said Will Uppington, CEO and co-founder, TruEra.

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GENERAL AI

PyTorch Lightning Creator, Lightning AI, Launches Open-Source Platform and Raises $40 Million Series B to Reinvent the Way AI is Built

Lightning AI | June 18, 2022

Lightning AI today unveiled the groundbreaking Lightning AI platform, backed by a $40 million Series B funding round, that completely reimagines how Artificial Intelligence (AI) products, services, and experiences are built. With Lightning AI’s new platform and framework, the company is introducing a frictionless way to build AI-powered products and services as apps composed of modular components that are seamlessly integrated and connected. Serving as the “operating system for AI,” Lightning AI’s platform ushers in a new era of accessibility and sophistication in the field of AI technology. The platform and underlying framework introduce a novel way to build AI by providing a unified experience that accelerates the deployment of AI technology across academic and enterprise use cases. Amid a fragmented machine learning ecosystem, Lightning AI’s suite of extensible open-source components and apps simplifies the underserved space and helps advance the widespread adoption of AI technology. “Launching this platform is a vital step for our company and the industry. “From day one, I wanted to reimagine the experience of building artificial intelligence beyond the current surfeit of tools and systems. Until now, there hasn’t been a way to build production-grade AI apps that takes into account the entire pipeline from development to production. Current options are limiting, highly prescriptive, and lack the flexibility needed to leverage AI in real-world scenarios. Imagine wanting to make a phone call and you’re simply handed the disparate parts that make up a working telephone, hoping that one day you’ll be able to make a phone call. Lightning AI takes the principles that have made PyTorch Lightning one of the fastest-growing open-source projects in history - simplicity, modularity, and sustainability - and applies them to the task of unifying the entire AI development and infrastructure lifecycle.” William Falcon, Lightning AI co-founder and CEO Lightning AI is the culmination of work that began in 2018 at the New York University CILVR Lab (Computational Intelligence, Learning, Vision, and Robotics) and Facebook AI Research. As a Ph.D. student working alongside advisers Kyunghyun Cho and Yann LeCun, William Falcon created and open-sourced the popular PyTorch Lightning framework. The explosive growth of the project within the AI community led Falcon to build a platform and company focused on eliminating barriers to widespread AI adoption. Grounded in the success of the PyTorch Lightning framework, the company built Grid, a platform for developing and training machine learning models on the cloud. The key to the company’s previous successes has been its unique ability to abstract away engineering infrastructure from the machine learning lifecycle while maintaining rigorous flexibility for experts who want full control over what they’re building. The Lightning AI platform and framework are powered by these groundbreaking advancements, enabling users to conceptualize, build, and deploy AI technology in a matter of weeks, compared to the months and years it would normally take. "We are excited about the development Lightning AI is leading by allowing AI-driven applications relevant to specific verticals come to life in a simple way. The partnership will bring further ease-of-use to customers and fit well with AWS’s industry, use-case and business problem driven approach,” said Dr. Kristof Schum, Global Segment Leader of Machine Learning at Amazon Web Services. $40M Series B Fuels Lightning AI Platform and Community Growth This $40 million Series B funding round, led by Coatue with participation from Index, Bain, First Minute Capital, and the Chainsmokers’ Mantis VC, brings the total raised to date to $58.6 million. Coatue General Partner Caryn Marooney has joined the board of directors, which also includes Index Ventures Partner Bryan Offutt. The capital will fuel further technology innovation, fund new AI research, and be invested back in the company’s growing user community and ecosystem. Lightning AI’s mission is to lower the barriers to AI adoption as the global AI market is skyrocketing and on track to exceed $500 billion by 2024. “As more companies across every sector leverage AI for crucial functions, they need a solution that makes it simple to consume, train, and use AI while also building applications free from vendor lock-in and specialized AI experts,” said Caryn Marooney, General Partner, Coatue. “Coatue immediately saw the potential and significance of Lightning AI’s mission to democratize AI. We look forward to supporting William and his team as they write a new playbook for AI deployment.” The Lightning-Fast Way to Build AI Apps Lightning AI allows researchers, data scientists, and software engineers to build, share and iterate on highly scalable, production-ready AI apps using the tools and technologies of their choice, regardless of their expertise. To solve any kind of AI problem from research to deployment and production-ready pipelines, users can simply group components of their choice into a Lightning App and customize the underlying code as needed. Lightning Apps can then be republished back into the community for future use, or kept private in users’ personal libraries. Lightning AI combines a wide variety of extant tools into a modular, intuitive platform for building AI applications in research, enterprise and personal contexts. It is the foundation of the growing Lightning ecosystem, which provides developers with a suite of ready-to-use tools and required infrastructure and compute resources, as well as community support for building AI applications. The Lightning AI platform is available now and includes: The new Lightning framework, which extends PyTorch Lightning’s simple, modular, and flexible design principles to the entire app development process A collection of tools and functionalities relevant to machine learning, including workflow scheduling for distributed computing, infrastructure-as-code, and connecting web UIs A gallery of AI apps, curated by the Lightning team, which can be used instantly or further built upon A library of components that add functionalities to users’ apps, such as extracting data from streaming video A hosting platform for running and maintaining private and public AI apps on the cloud The ability to build and run Lightning Apps on private cloud infrastructure or in an on-prem enterprise environment About Lightning AI Lightning AI is the company reimagining the way AI is built. After creating and releasing PyTorch Lightning in 2019, William Falcon launched Lightning AI to reshape the development of artificial intelligence products for commercial and academic use. Focusing on simplicity, sustainability, modularity, and extensibility, Lightning AI streamlines the lifecycle of machine learning development to expand widespread AI adoption. Its aim is to enable individual and enterprise users to build deployment-ready AI tools without having to hire experts or sink resources into in-house infrastructure.

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GENERAL AI

H2O.Ai Expands Snowflake Partnership for AI Transformations

H2O.ai | June 16, 2022

H2O.ai showcased a unique set of capabilities and use cases that enable rich insights by seamlessly connecting data and machine learning. Snowflake and H2O.ai bring together platforms for data and machine learning to help more clients develop with AI through a native connection that gives users access to H2O.ai's powerful machine learning capabilities straight from their Snowflake environment. Through several pre-built connections, customers may simply access the machine learning capabilities of H2O.ai from within the Snowflake Data Cloud for near real-time analysis. This shortens learning cycles, decreases processing time dramatically, assures that predictions are based on the most recent data, and makes these predictions accessible to any application built on top of Snowflake. Customers such as Infutor utilized the H2O.ai combination with Snowflake powered by Snowpark and Java User-Defined Functions (UDF) to avoid the need for additional platforms and AI-related expenses. "H2O.ai reduced our AI inference costs on Snowflake by 55X. H2O.ai partnership and support has made the integration that much more seamless and easy to leverage." Gary Walter, CEO of Infutor, a Verisk business H2O.ai is extending its partnership and dedication to Snowflake users in a number of vocations and sectors, including: Financial services Manufacturing Healthcare Tarik Dwiek, Head of Technology Alliances at Snowflake, said, “Our partnership with H2O.ai can help optimize the supply chain across multiple industries including manufacturing, telecom, banking and retail. With H2O AutoML, users have the ability to make, operate, and innovate for their customers and partners to reduce risks, improve customer experiences, drive growth, and improve efficiency.” Sri Ambati, CEO and founder, H2O.ai, said, “H2O AI Cloud is democratizing AI on Snowflake’s Data Cloud helping our customers personalize their offerings and bring efficient flows into their business. The tight-knit multi-cloud integration of H2O AI engines and AI App Stores drives consumption on Snowflake Data Cloud reducing costs for customers and powers organization-wide transformation needed to adapt quickly.”

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