VentureBeat presents AI Innovation Awards nominees at Transform 2021

There is a consistent theme that runs through the agenda for VentureBeat’s Transform 2021 virtual conference, and that is artificial intelligence and data analytics are being used in many different areas and in creative ways. AI is being used in the field of fitness, apparel, energy, and real estate. It’s expected that social media companies founded in the past ten or so years will be using AI and other advanced technologies, but it is extremely reassuring when a company that has served generations is still keeping up with the latest technologies — and doing well.

AI is a complex field and the technology is ever-evolving, and VentureBeat has the front-row seat. There is research pushing boundaries of what is considered possible. There are new products transforming how people work, live, and play. Amidst all of that, there are organizations and individuals working on solving certain challenges in ways that are innovative and creative. That is the purpose of the AI Innovation Awards, where emergent, compelling, and influential work gets recognized. For the third annual AI Innovation Awards honored people and companies engaged in compelling and influential work in five areas: natural language processing and understanding, business applications, edge innovation, “Startup Spotlight”, and AI for Good.

A nominating committee helped the editorial team with the selections. The members of the nominating committee for this year’s AI Innovation Awards were: Vijoy Pandey, the vice-president of engineering and CTO of cloud and distributed systems at Cisco; Raffael Marty, senior vice-president of product, cybersecurity, at Connectwise, and the former chief research and intelligence officer at Forcepoint; and Stacey Shulman, vice-president of the IoT Group and general manager of Health, Life Sciences and Emerging Technologies at Intel. They were generous with their time and knowledge, and provided the editorial team with an intriguing list of individuals and organizations to consider.

Natural language processing/understanding

Many things become possible when machines can understand the language people speak and write. Smart assistants can handle more tasks and are responsible for numerous tasks in different industries. Translation services create a more global world. Productivity tools are more effective. There are so many different use cases, and natural language processing — which includes natural language understanding, natural Language Generation, and Natural Language Interaction — makes it all work.

Primer uses machine learning techniques to help parse and collate a large number of documents across several languages in order to facilitate further investigation. Users feed Primer’s software a stream of documents, and it automatically summarizes what it determines to be the most important information out of that haystack of data. Users are then able to filter by topic, event, and other categories to drill down into the information Primer collected so they can go beyond the automatically generated headlines. Primer’s NLP platform is used by a number of United States federal agencies, and recently raised $110 million in funding.

EleutherAI was founded on the idea of making AI technology that would be open source — and the first one on deck was making am open source model replicating the GPT-3 work from OpenAI. This past March, the EleutherAI team released two trained GPT-style language models, GPT-Neo 1.3B and GPT-Neo 2.7B. The code and the trained models are open sourced under the MIT license and can be used for free via Hugging Face’s Transformers platform. This team is pushing the envelope of NLP research through an open source approach. The platform also makes

Dr. Pei Wang of Temple University was nominated for his Nonaxiomatic Reasoning Engine and its application to NLP. The NARS project, which Wang has been working on for approximately 20 years, attempts to uniformly explain and reproduce many cognitive facilities — including reasoning, learning, and planning — to generate a unified theory, model, and system for AI. The nomination is for Wang’s persistence on his symbolic approach to AI, now being absorbed widely in other applications.

Hugging Face is democratizing NLP by building an open source community for sharing models, datasets, and other resources. The team is conducting research, creating NLP libraries such as Transformers and Tokenizers, and releasing tools to leverage models such as BERT, XLNet, and GPT-2. The nominating committee specifically noted that Sasha Rush — Associate Professor at Cornell Tech — is one of the brains behind Hugging Face.

CoPilot, the project launched by GitHub that acts as a pair programmer and helps developers write better code, may be brand new, but it jumped into the nomination lists because of the way it suggests new code and learns the developer’s coding style. Copilot uses OpenAI Codex, which may be more capable than GPT-3 in terms of programming code.

Business applications

It’s interesting to explore new ideas and compelling research, but the true impact of AI comes from the practical applications. Low-code/no-code tools are helping non-developers create applications and data pipelines. Robotic process automation streamlines workflows and makes business operations more efficient. Intelligent software and services help solve real-world problems. This is where life starts to feel like something out of science-fiction.

Incorta offers all-in-one data crunching service for customers to analyze corporate data spread across multiple databases and then render it all into charts and graphics. The company’s service help organizations acquire, enrich, analyze, and act upon business data — upwards of tens of billions of rows of data become “analytics-ready” without the need to pre-aggregate, reshape, or transform the data in any way. Incorta helps reduce data bloat in organizations.

Dr. Sheila Nirenberg, a neuroscientist for Cornell Medical School, has successfully “cracked the code” for how the retina sends signals to the brain. Her work, combined with optogenetics, help blind people see again. While that is impressive on its own, Dr. Nirenberg was nominated because of the way she has taken what she learned in this field and applied them into the AI space. Her company, Nirenberg Neuroscience, applies the “neural code approach” from a mamalian retina to greatly reduce the amount of training data needed for activity based detection models. This new approach will allow very hard-to-train models to become easy to train with supervised learning.

DeepSee.ai automates manual business processes by combining open source and proprietary machine learning, linguistic comparison and prediction techniques, and sentiment analysis. DeepSee’s cloud-hosted platform captures, extracts, normalizes, labels, and analyzes unstructured data, and then surfaces trends and patterns for review. DeepSee provides a pipeline to deliver AI-generated templates, rules, and logic.

Pilot applies AI to the field of financial tech — fintech — and provides context-specific reporting, insights, and expertise for businesses that may not have an in-depth finance team. Pilot’s software provides automated visibility, error management, and predictive insights to help customers make better budgeting and spending decisions.

Indico allows customers to automate the intake and analysis of document- and image-based workflows. The platform, which can be deployed in private cloud or on-premises environments or as a managed service, ingests PDFs, Word documents, and other unstructured text, images, and documents. Once ingested, the data is processed using natural language understanding models and chained together into pipelines to perform data classification, extraction, and comparison. Indico applies transfer learning — where a model developed for one task is used for another task — to deploy unstructured content more effectively.

Edge

Last year’s awards focused on computer vision, but this year, edge AI is becoming a bigger topic of conversation. The pendulum swings regularly between processing all the data in a centralized location and processing data right on the device. A farmer standing in the middle of the field doesn’t have WiFi — making it really difficult to use the data collected by sensors and other smart devices. This is a situation that is going to be familiar across multiple industries, as the Internet of Things and near ubiquitous network capabilities promised by 5G creates new opportunities with real-time data.

Autonomy Institute is a cooperative research consortium focused on advancing and accelerating autonomy and AI at the edge. The consortium announced a pilot program at the Texas Military Department’s Camp Mabry location in Austin, Texas to build out a test smart city environment to optimize traffic management, autonomous cars, industrial robotics, autonomous delivery, 911 drones, and automated road and bridge inspection. The program deploys the Public Infrastructure Network Node (PINN), a unified open standard supporting 5G wireless, edge computing, radar, lidar, enhanced HPS, and intelligent transportation systems (ITS). PINN clusters in a city deployment could be positioned to collect information from the sensors and cameras at a street intersection. Edge computing using PINN is what will make it possible to process all of the signals and do something about it, such as making the traffic lights change as a car approaches the intersection.

DEKA Research’s ROXO bot was built on top of the iBot wheelchair base — a wheelchair that can climb stairs and lift riders to eye level with others — to fill inventor Dean Kamen’s (person behind the Segway) vision to make wheelchairs more affordable. Removing the chair attachment and replacing with a delivery pod turned the robot into a hardened delivery solution that can drive over nearly any terrain and can climb stairs. Under a partnership with FedEx, the ROXO bot provides package delivery.

Edgeworx turns any computing device — regardless of compute and resources, or operating system — into an edge software platform to allow developers to simply and securely deploy, manage, and orchestration applications from cloud to edge. Its technology was designed from the ground up to be the infrastructure layer for edge devices, and to interface with legacy systems and cloud and data center. Edgeworx enables customers to run real software on edge devices with the same level of security and remote control as they would have in a cloud environment.

SambaNova, which was founded by Oracle and Sun Microsystems veteran Rodrigo Liang and Stanford professors Kunle Olukotun and Chris Ré, develops chips for AI workloads. AI accelerators are a type of specialized hardware designed to speed up AI applications such as neural networks, deep learning, and various forms of machine learning from the data center to the edge.

Multiply Labs, founded by two MIT alumni, has helped pharmaceutical companies produce biologic drugs with its robotic manufacturing platform. Operating at the intersection of robotics and pharmaceutical manufacturing, the company makes the production of individualized drugs at industrial scale possible through automation.

Startup Spotlight

There are many players in the field, from small startups working on one specific idea, academic and private research laboratories pushing the boundaries of what we can do, and large well-funded companies exploring the answers to a broad array of questions. This category focuses on companies that work with AI, have raised $35 million or less in funding, and have been in operation for no more than two years. This award spotlights the startup’s potential to make a significant contribution to the field in the years to come.

Apiiro’s Code Risk Platform accelerates development by allowing organizations to identify and prioritize risky code changes before they become part of the development pipeline. Apiiro can identify and fix security problems during the development process because it analyzes the developer’s behavior to identify potentially risky behaviors that could impact the organization. The platfrom can learn historical behavior of application, infrastructure-as-code, open source components.

Medical Informatics Corporation created Sickbay, a technology platform that uses data to help collect information on the patient. The medical environment is awash in data but they aren’t stored in a place that the medical team can access it.

Udyogyantra is focused on food safety and supply chain transparency. The SmartQC system standardizes and improves food quality by providing real-time insights such as temperature of food, quantity, and consistency

Parity analyzes documentation, identifies risk zones, and recommends methods to mitigate harmful model qualities. Parity offers services designed to identify and remove bias from A.I.

TabNine is based around deep learning AI that studies publicly shared code, primarily through scanning GitHub repos, to suggest time-saving code completions, error predictions and generally make coding better. TabNine also plugs into the preferred IDE.

AI for Good

The AI for Good award honors AI-driven technology, applications, and activism goes beyond just making things easier and faster to making a different. This category looks at people and companies that work to protect human lives, fight injustice, and otherwise improve society. There are ways AI is arguably making the world a better place — or if not better, then at least safer. This award is for AI technology, the application of AI, or advocacy or activism in the field of AI that protects or improves human lives or operates to fight injustice, improve equality, and better serve humanity.

Jake Porway, the founder of DataKind, is pushing to help non-profits connect with experts in the field. As more data scientists get involved, they are looking for opportunities to make suggestions about product development or strategy after analyzing data in a business setting. This is a case where the platform exists specifically to harness people’s know-how for causes that go beyond corporate objectives.

The work Carla Gomes has done in AI has benefitted society: her work on hydrodam locations was in coordination with Brazil. The effort made sure that it hit the right balance between methane production / environmental damage and low cost electricity generation.

David Rolnick wrote a big paper about the various ways that AI can help with climate change that was widely circulated and discussed. In nearly every climate change workshop that has come around in recen months, there is now a bit about using AI technologies. That change came about because of David Rolnick.

The Internet Watch Foundation is a team of 21 individuals who work out of Watch Foundation’s office in Cambridgeshire. These individuals spend hours trawling through images and videos containing child sexual abuse. And, each time they find a photo or piece of footage that is dangerous — it needs to be be assessed and labeled. Last year alone the team identified 153,383 web pages with links to child sexual abuse imagery. This creates a vast database that can then be shared internationally in an attempt to stem the flow of abuse. These classifications are also used to work out how long someone convicted of a crime should be sentenced for.

Folding@Home built the first Exascale Edge compute platform performing AI operations. Over a “Million citizen scientists” (which is really just people installing F@H on their computers) — takes part in which essentially is worlds largest supercomputer. The company platform is compiled and optimized for dozens and dozens of architectures, different Intel, AMD, and then dozens of GPU types/models. Folding@Home solved quite a few basic problems for SAR-CoV-2 which made it possible to begin vaccine production.

The winners will be announced in the morning of July 16 as part of the activities wrapping up Transform 2021.