AI Trends and Predictions to Watch out For This 2019
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The concept of Artificial Intelligence (AI) or Machine Intelligence is no more an unknown or unexplored concept to us and all the thanks go to Siri, Alexa, Cortana, and Google Assistant for being live examples. Even though these assistants evolved recently, but AI was there for quite some time. Right from filtering our mailboxes to AI-powered chatbots or AI enabled recommendations; we were always surrounded by Artificial Intelligence. AI has also impacted various fields, like aiding in synthesizing new chemicals, medical diagnoses, identifying the faces of criminals in a huge crowd, self- driving cars, and even creating new works of art. Even though there is a lot of debate and discussion going on about the future of AI but for now Artificial Intelligence is here to stay.
AI has many limitations of its own, such as lack of human-like analyzing or decision-making ability, and requires supervision, but AI is not only impacting our daily lives but also augmenting businesses like - in many ways. AI has shown immense potential in businesses by making it possible to reach the correct set of customers, engaging and nurturing them, and eventually impacting ROIs. A PWC study report stated that AI has the potential to offer $15.7 trillion to the global economy by 2030.
As this is the end of 2018, the internet is flooded with predictions for AI for 2019. This blog post is also going to focus on the same but to befriend the technology rather than jotting down the limitations or disadvantages of Artificial Intelligence.
We are quite familiar with AI assistants like Siri, Alexa, Cortana or Google Assistant, whose robotic intelligence helps us make our daily life easier. In a recent survey by Pegasystems of 6000 participants, 70per cent of them are afraid of AI and 25per cent believes it will enslave humanity by taking over the world. While 31peer cent also believes humans will be replaced by robots on the job, some contend that AI assistance on the job would help improve work/life balance. AI-driven predictions are at work to make everything precise, convenient and to make the experience smooth.
Along with our daily lives, AI is all set to have an effect on our work life as well. AI assistance will become increasingly useful as they are continuously learning to anticipate consumers behavior. Data gathered from users are allowing designers to understand exactly which features are adding value. 2019 is a calendar year where we will use AI assistance more than ever, right from ordering food or arranging our planners.
There is clearly tremendous power in the thinking, learning, and creative potential of modern AI, but the concern is:
How can we impose sensibilities while it's making a decision about, say, a customer?
Can we trust it?
What it will do with our data?
How it makes its decisions when it comes to such issues?
For humans, it's their analyzing ability or intuition that helps in taking decisions, but in AI, the ability to draw connections, make inferences and taking decisions is quite mathematical rather than an analogy. There are two concepts on what form of control an AI could take: Opaque AI and Transparent (or Trusted) AI. Opaque AI includes neural networks, deep learning, genetic algorithms, ensemble models to take a decision and the “logic” behind their predictions and decisions can’t be easily expressed. Whereas on the other hand, Transparent AI, can explain how it came to a decision in a way that is understandable to a human. IBM recently launched a technology, AI OpenScale, which aids in tracing the decision taking the ability of an AI. In another instance, Europe's General Data Protection Regulation has ensured their citizens' protection against the AI enabled decisions which might have a legal or significant impact of their lives. This 2019, we're likely to see an increased emphasis on the transparency of AI which will build the AI enabled more responsible.
Organizations across the globe are adapting Artificial Intelligence in their systems but the process of cognification is a major concern they are facing. Theoretically, everything is getting smarter and intelligent but the existing computer chips are not compatible enough and are slowing down the process. Even most advanced CPUs are incapable to improve the speed of training an AI model. Nigel Toon, Co-Founder of Graphcore, said, “What we heard universally was that current hardware was holding developers back.” Graphcore, the Bristol-based startup has built a new chip to help speed up the process-hogging, resource-intensive deployment of AI. This chip is capable to handle advanced AI algorithms, which are up to ten times faster than current processors.
In near future, chip manufacturers such as Intel, ARM, NVIDIA, MediaTek, AMD, and Qualcomm will make specialized AI enabled chips to speed up the execution of an application.
You must be familiar with the concept of AI-based recommendations. AI helps in recommending what you might need or would like to search, buy, read next, based on your searching and browsing pattern but 2019 has something exciting in store. AI will be able to better recommend products based on sentiment and tone.
We have already come across similar Artificial Intelligence integration of IBM Watson-powered gift concierge in Gifts retailer 1800Flowers' product GWYN - Gifts When You Need. Based on product-choosing and purchasing processes by pulling suggestions from 1800Flowers.com, GWYN interacts with users via natural language and interprets the inquiry and follow up with a series of relevant questions, like the occasion type or sentiment, to recommend the perfect product.
Machine Learning and IoT Sensor Analytics
Machine learning is a subset application of Artificial Intelligence (AI) that enables a system to automatically learn and improve from experience without being explicitly programmed. As this capability applies to a range of data, problems, and challenges across the organizations, 'The Global Ecosystem AI Study' suggests that in the upcoming year, ML will highly influence the growth of AI.
In 2019, AI will meet the IoT at the edge computing layer. Due to the rise in IoT implementations, IoT Sensor Analytics will also see strong growth as well. The rapid development of connected devices and IoT applications has driven enterprises toward real-time edge analytics. An edge computing IoT network running on-device Machine Learning and AI Models. It's capable of achieving significantly faster predictions for critical IoT applications.
AI in Cyber Defense
By 2021, cybercrime will cost the world upwards of $6 trillion annually. Tech security is a huge menace for organizations as cybercriminals are active targets cloud infrastructure, software-as-a-service (SaaS) platforms, and the Internet of Things (IoT) devices. AI has evolved to be a strong security tool to fight off such cyber threats and block potential hackers. AI, which involves computer algorithms, is empowered to pick up cyber threats by learning, interpret patterns and make predictions. It figures out abnormal activities and defends the system at an early stage before it becomes uncontrollable.
In Black Hat cybersecurity conference in Las Vegas, many organizations claimed that they are using ML and AI to help make the world a better, safer place. Using AI can help automate threat detection and potentially help identify threats more efficiently than other software-driven approaches. But where some companies like Darktrace are deploying these technologies to detect online enemies, there are others who aren't paying enough attention to this. In the conference, Holly Stewart and Jugal Parikh from Microsoft strongly suggested that overreliance on a single algorithm to drive a security system is highly risky. 2019 will see more and more organizations considering AI as a cyber-bodyguard.
AI in the Healthcare Industry
In this age of technology, Artificial Intelligence knows no bounds. Once thought a futuristic threat to humankind, AI is changing and saving lives. Not intended to replace clinicians or over clinical judgment, AI serves the purpose to enhance and complement the very human interaction a provider and patient.
In healthcare, AI is changing the game with its applications in decision support, image analysis, and patient triage. With their ability to reduce variation and duplicate testing decision support systems quickly decipher large amounts of data within the electronic medical record.
AI technology is also taking the uncertainty out of viewing patients' scan by highlighting problem areas on images, aiding in the screening in the diagnosis process. Artificial intelligence helps with the issue of physician burnout by collecting patient data via an app or text message. Chatbots now asks patients a series of questions regarding their symptoms taking the guesswork out of self-diagnosis and savings both, the patient and provider, time and money. With the AI integration working smarter enables solutions to a variety of issues for patients, hospitals, and the healthcare industry.
AI Industry in India
The global AI economy is just starting to boom. Globally, the largest ecosystem is USA which homes almost 3,000 high-growth AI tech businesses. The next largest hotspot for deals in the United Kingdom with 1179 deals, Canada with 870 and India with 615. The USA, China, Israel & India have the highest levels of capital investment.
Currently, there are various start-ups working on AI and machine learning domains. Global Investors have spent almost $150 million dollars in India's AI sector and the number has been growing since 2016.
AI industry in India needs capital and manpower. Even though India is home to a large pool of talent but pro manpower in AI is still a half-filled space. There are various Artificial Intelligence course and Artificial Intelligence Training available for professionals but experts believe that it’s high time that colleges and universities in India start preparing the future workforce suitable to cope up with the top technologies. Considering this huge gap, AICTE, the government body which regulates professional education in India has recently added AI, Machine Learning, IoT and other relevant subjects in the B.Tech courses.