Lucd's View on Gartner Top 10 Strategic Technology Trends for 2020
At its Symposium last week in Orlando, Gartner issued its Top 10 Strategic Technology Trends for 2020. They grouped them into two categories of 5 trends. The first category was “People-Centric” trends, the second category was “Smart Spaces” trends. The following is that top 10 as well as Lucd’s view on that trend.
Gartner input that the goal of Hyperautomation is to automate anything that can be automated and that the No. 1 use case for AI is process automation.
Lucd View We can debate whether the No. 1 use case for AI is process automation (new and better ways of doing business). It is certainly one of the top 3, along with new and better products and services and new and better customer interactions.
However, Lucd’s view is that while AI certainly does support Hyperautomation, the process of learning from data to drive business outcomes (Enterprise AI) can use quite a bit of automation itself. It was clear from attending sessions at the Symposium that many people in business do not understand AI and that the tools to create AI are available yet complicated. That is why Lucd is heavily investing in “Hyperautomating” the process of creating AI for business (Enterprise AI) so that more business people can understand and interact with Data Scientists via easier to use tools that still leverage open source AI innovation.
Multiexperience Gartner inputs that by 2021, one third of enterprises will have deployed a multi-experience development platform.
Lucd View We wholeheartedly agree. Lucd is the first Enterprise AI platform that is leveraging an immersive UI for interfacing with data, transforming data and training models. In Gartner’s Cool Vendors in Enterprise AI Governance and Ethical Response Published: 10 October 2019 and where Lucd is identified as a Cool Vendor, Gartner states: “Lucd’s visualization can run on touch-enabled laptops or large-screen monitors, because the vendor leverages the Unity gaming engine to enable real-time 3D immersive collaboration. This approach makes the data and outcomes exciting and easily consumable.
Democratization Gartner states that while 30% of organizations will deal with “Shadow AI” by 2022, Democratization is about empowering everyone. Gartner states the challenges are lack of AI skills, dealing with uncontrolled shadow AI, insufficient data, and inability to empower developers.
Lucd View In order to democratize, the barrier to skills must be lowered, disparate organizations must find it easier to leverage a centralized capability than doing “shadow” work, data must be aggregated and fused, and developers need to be able to leverage the open models of their choice. Lucd provides these exact capabilities.
Human Augmentation Gartner states that by 2025, organizations will architecting humans themselves by adopting human augmentation technologies.
Lucd View 2025 is a stretch for a 2020 top trend, however, the point is valid and provides an important view of the future. The bottom line right now is that AI is about augmenting people and Lucd completely agrees. Our customers are focusing on leveraging AI to augment people so that they can provide better customer experiences, products and services and ways of doing business.
Transparency and Traceability Gartner states that by 2023, 75% of large organizations will hire AI specialists in behavior forensic, privacy, and trust to reduce brand and reputation risk.
Lucd View This is so critically important to all of us humans going forward. So important that it is better for organizations to build AI with those transparency and traceability characteristics embedded in the platform itself. That is why the Lucd platform has built its platform from the ground up with these capabilities.
Empowered Edge Gartner states that by 2023 more than 50% of enterprise-generated data will be generated outside the cloud or data center. And that is up from just 10% in 2019.
Lucd View Bottom line, data is everywhere. Data that you have (in the cloud or data center); data that you can collect (more and more from the internet of everything); and data that you can get access to (public sources of data). And that data comes in all shapes and modalities. Any type of Enterprise AI initiative has to be able to handle all types of data, from everywhere and at scale. That is why Lucd’s architecture supports its multi-modal ingest capability and Petabyte scale Unified Data Space.
Distributed Cloud Gartner positions Distributed Cloud as the next generation that fixes Hybrid Cloud problems.
Lucd View Lucd has seen for some time that while the mega cloud vendors have a very important role to play in the future of all things related to information and communications technology, they are not the be all and end all for every particular challenge and opportunity. In presentations at Symposium, statistics were given where many organizations develop Enterprise AI on premise, many others leverage the cloud only when GPU requirements are necessary for big training requirements. Lucd agrees that the Distributed Cloud is the future. And while the exact architecture is tbd, right now, that starts with Kubernetes capability and other infrastructure approaches that allow Enterprise AI to be deployed per a customer requirement and independent of a specific locked in approach.
Autonomous Things Gartner states that by 2025, 12% of vehicles will have Level 3 or higher autonomous capability.
Lucd View More than a lot has been written about Autonomous things. But, a core requirement is an ability for a business to leverage Computer Vision and Reinforcement Learning capabilities as part of its Enterprise AI capabilities. Enterprise AI is and will be more than just a particular classification or regression problem. More and more, capabilities including NLP, computer vision, collaborative filtering, RL, and Generative Adversarial Networks will be table stakes. The only way to really do this and to keep up with the advancements is to stick with open architectures and open source approaches to Enterprise AI. Lucd strategically aligns to this architectural approach.
Practical Blockchain Gartner states that by 2023, blockchain will support the global movement of $2 Trillion worth of goods and services.
Lucd View Blockchain holds great promise for verifying goods and services but also verifying a data pipeline used in Enterprise AI. However, before this, there are practical things that businesses can do to verify data lineage from source to training and deploying a model. Lucd will look to leverage blockchain in the future but implements those practical capabilities now.
AI Security Gartner states that by 2022, 30% of all cyber attacks will focus on training data poisoning, model theft, and adversarial samples. Specifically, the AI pipeline as constructed today are at risk.
Lucd View Lucd was constructed with this awareness. It is hard to back-fill a pipeline to secure it. It is another reason why Lucd was selected as a Cool Vendor. As Gartner states in its 2019 Cool Vendor report… “ Why Cool: The Lucd enterprise-class AI platform is built from the ground up with considerations for compliance, security and governance. This cool vendor demonstrates innovation in core capabilities — AutoML, visualization, scalability and patented AI technologies — necessary for the AI success. Its platform differentiates with strong governance features — automation for compliance, bias prevention and monitoring for semantic data drift. The Lucd platform provides provenance, audit trail and traceability, as well as version control of the model and training data — hard to find together elsewhere, but critical for model reproducability. Lucd’s platform’s most unique feature is its application-level security, implemented with cell-level access control. Given that there may be many stakeholders in an enterprise, it is often imperative for each of them to use only what they are entitled to. Lucd’s platform has a mechanism to guard against unlawful, unethical and non-compliant results when it comes to engineered features for a model.”