The AIconics are the world’s only independently-judged awards celebrating the drive, innovation and hard work in the international AI Community. A panel of 20 judges from around the world thoroughly reviewed competitive entries from the leading innovators in the AI Space.
Here are the 2018 winners:
Best Application of AI for Sales & Marketing
RTB House is a global company that provides state-of-the-art retargeting technology for top brands worldwide. Its proprietary ad buying engine is the first and only in the world to be powered entirely by deep learning algorithms, enabling advertisers to generate outstanding results and reach their short, mid and long-term goals.
Best Innovation in AI Hardware
Pure Storage helps innovators build a better world with data. Pure's data solutions enable SaaS companies, cloud service providers, and enterprise and public sector customers to deliver real-time, secure data to power their mission-critical production, DevOps, and modern analytics environments in a multi-cloud environment.
Best Innovation in Robotic Process Automation
UiPath provides a complete software platform helping organizations automate business processes. The company's mission is to eradicate tedious, repetitive tasks and let software robots do the grunt work. They enable businesses and organizations to develop an agile digital workforce by providing a state-of-the-art platform for software robots orchestration. Their products automate across all internal or web-based applications/databases and have unmatched solutions for Citrix, SAP and BPO automation.
Best Application of AI in Financial Services
WorkFusion's Intelligent Automation empowers enterprise operations to digitize. WorkFusion combines robotic process automation (RPA), AI-powered cognitive automation, workflow, intelligent conversational agents, crowdsourcing and analytics into enterprise-grade products purpose-built for operations professionals. These capabilities let enterprise leaders digitize their operation, exponentially increasing productivity and improving service delivery.
Best Intelligent Assistant Innovation
Artificial Solutions® is the leading specialist in Natural Language Interaction (NLI), a form of Artificial Intelligence that allows people to converse with applications and electronic devices in free-format, natural language, using speech, text, touch or gesture. Delivered through Teneo® – an ultra-rapid NLI development and analytics platform – it allows business users and developers to collaborate on creating sophisticated, humanlike natural language applications in record time without the need for specialist linguistic skills.
Best Innovation in Deep Learning
IBM Watson Studio
IBM’s experiment-centric deep learning service within Watson Studio allows data scientists to visually design their neural networks and scale out their training runs while auto-allocation means paying only for the resources utilized. Watson Studio accelerates the machine and deep learning workflows required to infuse AI into your business to drive innovation. It provides a suite of tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data. Build, train, deploy and manage AI models at scale, and prepare and analyze data, in a single, integrated environment.
Best Innovation in Natural Language Processing
Clarabridge helps hundreds of the world's leading brands understand and improve their customer experience. Using advanced text analytics, Clarabridge transforms survey, social, voice and all other forms of customer feedback into intelligence used to empower confident, decisive action across the business.
Best AI Start-Up
Luminance helps lawyers to categorise, review and analyse thousands of documents at speeds no human can match. With AI taking the burden of low-level cognitive tasks – like those common in due diligence, compliance, insurance or in-house contract management – lawyers can optimise their practice, working smarter, faster and more effectively.
Best Application of AI in the Enterprise
LiveTiles is defining the market for the intelligent workplace by giving developers and business users tools to easily create dashboards, employee portals, and corporate intranets that can be further enhanced by artificial intelligence and analytics features.
Best AI Application in Healthcare
Aifred Health is using AI techniques to develop a clinical decision aid for physicians to improve treatment efficacy for individuals suffering from depression. The foundation of this clinical tool is the data collected by researchers investigating patient response to depression treatments in clinical trials .
Artificial Intelligence and IT Service Management
As AI transforms the workplace, IT Service Management will both enable this process as well as be transformed itself through the new efficiencies coming in.
Not just the stuff of sci-fi films anymore, AI is transforming technology in people’s daily lives, Amazon’s Alexa and AmazonGo being important examples. According to a Gartner report, there are three key requirements that define AI:
It needs to be able to adapt its behavior based on experience.
It needs to be able to learn without being solely dependent on human instructions.
It needs to be able to come up with unanticipated results.
Based on these criteria, the AI that we deal with regularly, like Siri and Alexa, are examples of ‘weak AI’, as they are built to accomplish very specific tasks. ‘Strong AI’ or ‘General AI’, which is the end game, is still a distant dream.
Nonetheless, weak (or narrow) AI by itself packs in enough exciting potential to revolutionize the workplace. The opportunities it presents can, however, be squandered if its deployment is done without proper human governance. This governance will largely fall into the hands of corporate IT Service Management (ITSM) teams.
AI’s role in the ITSM revolution
At the same time, AI has the potential to transform ITSM too, allowing staff to delegate mundane tasks to AI software and focus on more strategic issues. A learning, conversational AI experience will be critical for AI technology to succeed, and will revolutionize ITSM in the following key ways:
An AI-automated front line
Currently, risk and uncertainty is rife in old-style self-service portals, making companies reluctant to divert their human ITSM frontline resources away from basic phone handling. AI-enabled chatbots can help develop automated ITSM solutions that are better at customer query interpretation, assistance without human intervention and providing a personalized end-user experience.
Good ITSM operates many vital ‘back-end’ processes like incident management and change management that keep IT systems running. AI can not only make this process more efficient – for instance, when connected to IoT devices it can be notified instantly if a smart device starts malfunctioning, without the end-user having to report it – but also make business aware of ITSM’s important place as an enabler.
All knowing AI
AI-powered ITSM can efficiently handle large volumes of data and decipher patterns, resulting in real-time insights, predictions of problems and recommendations to fix them. Plus, it can source answers to difficult queries from across the Internet as well as pool data from multiple organizations to provide better solutions.
Ultimately, humans will remain vital for delivering AI-enhanced IT services. AI’s rapid evolution will allow it to work alongside humans to create a more efficient workplace. It will also allow IT staff to become business enablers and productivity transformers, while technology does the heavy lifting.
Healthcare’s AI Market to hit $6.6 bn by 2021, says Accenture
The projected 1000% increase in the healthcare AI market from 2014 to 2021 is driven by factors like greater consumer acceptance, change in healthcare models and rapid increase in investments.
A new Accenture report, which looked at investments, revenue growth and acquisitions in the AI space, predicts that the healthcare AI market will reach $6.6 billion by 2021 from just $600 million in 2014.
The rapid growth is driven by factors like the move to population health, and greater acceptance of machines in healthcare delivery by consumers, driven by experiences in other services.
Accenture’s survey of over 3000 consumers shows that one in five US patients have already used AI-powered healthcare services, like robots, virtual clinicians, and home-based diagnostics.
In keeping with the move in the wider healthcare industry from volume of care to value-based models, business and venture funds are funding development of products and systems based on AI.
Examples: Use of AI by Anthem and Cigna to curtail opioid addiction; funding by Optum Ventures of the startup Buoy Health that has developed an AI-powered digital health assistant that helps patients better understand symptoms and advises on next steps.
Regulators are stepping up approvals of AI systems and related products.
Example: Approval of three of the seven robotics products developed by Bionik Laboratories, a venture whose solutions have been used for treating neurological disorders in over 200 hospitals in 20 countries.
The future of AI in healthcare
According to Bionik’s CEO, Eric Dusseux, there will be a steady evolution of AI both in the medical industry and beyond. Humans have long relied on technology to improve efficiency, productivity and process quality. Innovations like AI, machine learning and brain-computer interfaces will encourage continued use of technology in the medical space to further optimize patient treatment and care.
From facial recognition devices to personalized media, AI is expected to finally start affecting people’s lives in a truly meaningful way in 2018.
Since at least Turing’s time in 1950, intelligent computers has fascinated people. But it has taken decades for the right combination of factors to come together to move AI from concept to an increasingly ubiquitous reality. After a lot of talk in 2017, it is in 2018 that data generated because of mass use of Internet-connected devices, and algorithms that recognize patterns in this data, will lead to tangible ways in which AI affects all our lives. Some of these expected developments are:
Smart virtual assistants – Personal assistants based on AI will become smarter and more affordable. They will learn our daily routines and handle simple, but useful, chores like ordering groceries.
Multiple voice-based gadgets – The popularity of voice-based assistants will result in many devices at home across platforms. There’s exciting potential, but possible chaos expected as well.
Practical use of facial recognition – Going beyond security and biometric capabilities, facial recognition will start replacing credit cards, driver’s licenses and barcodes. No need to even line up at the payment counter at a store.
Basic AI terminology becoming commonplace – As AI permeates the enterprise, everyone from CEO through middle managers to frontline employees will start becoming conversant in basic terminology. This will help demystify the technology and open up possibilities.
Personalized media – Forget identifying songs that you will like – new services could start creating music from scratch based on your tastes.
Tailored news and market reports – Reports that don’t just recap market performance, but explain your portfolio performance, at any time, will soon be a reality. Newsrooms will also use AI in more innovative ways.
Empathetic computers – Multi-part conversations, more comprehensive answers, and insightful suggestions, will be expected from new smartphones and smart speakers. This will be partly driven just by the increasing amount of time these devices spend around us.
Wide use in healthcare – By end-2018, nearly half of leading healthcare systems will have adopted some form of AI within their diagnostic groups, not just in medical specialties, but even in hospital operations, solutions for population health and clinical specialties. The way patients experience healthcare globally will truly begin its transformation in 2018.
The two cutting-edge technologies of today, artificial intelligence, and blockchain could unlock new frontiers if used in sync.
AI: The theory and practice of building machines capable of performing tasks that require intelligence, using technologies like machine learning, artificial neural networks, and deep learning.
Blockchain: A new filing system for digital information, which stores data in an encrypted, distributed ledger format. Encryption and distribution of data across many different computers enable the creation of tamper-proof, highly robust databases that can be read and updated only by those with permission.
The theoretical benefits of combining these two technologies haven’t translated as yet into real-world applications, but this could change soon. Three ways why this should happen are:
AI and encryption work well together
The cost of securing the vast amounts of sensitive, personal data (think healthcare systems, banks or even Netflix) handled by AI systems is immense. Blockchain databases hold information in an encrypted state, requiring only the safety of the private keys – a few kilobytes of data – lowering the costs of handling AI data tremendously.
Conversely, an emerging field of AI is concerned with building algorithms that can process data while still encrypted. This complements the safety of blockchains, by eliminating the risk of exposure of unencrypted data.
Blockchain can help us track, understand and explain AI decisions
AI systems make complex decisions by assessing a large number of variables. In areas like banking or the retail industry, these still need to be audited for accuracy by humans, which can be very difficult. If decisions are recorded, on a datapoint-by-datapoint basis, on a blockchain, it makes it far simpler for them to be audited, with the confidence that the record has not been tampered with between the recording of the information and the start of the audit process. This is a step towards achieving the level of transparency and insight into robot minds that will be needed to gain public trust.
AI can manage blockchains more efficiently than human or conventional computers
Conventional ‘stupid’ computers apply brute force when working with encrypted blockchain data, requiring large amounts of computer processing power. AI can perform such tasks – like verification of Bitcoin transactions – more intelligently by becoming adept at cracking codes almost instantaneously if fed the right training data.
Clearly, the two ground-breaking technologies have the potential to become even more revolutionary together. They can enhance each other’s capabilities while offering better oversight and accountability.