AI far surpasses the hype of blockchain, crypto, quantum computing, and so many others since in the world of tech trends, artificial intelligence is already here with machine learning, algorithms and the sea of predictive analytics that actualizes Big Data.
Indeed here we are not talking about the dangers of AI to humanity, but about how it’s scaling in the real world. There are some notable AI trends that will change the world in 2019.
1. Amazon Go stores Upend Retail
Amazon Go is the model of the future store, and apparently, they plan to open at least 3,000 of them by 2021. Here is where computer vision, a virtual point of sale with QR code sign-in and cameras and LiDAR all work together in a coherent whole, making cashiers and many staff obsolete.
This is the very pinnacle of AI in a retail setting, and Amazon has been working on this for years, and finally, we are going to experience it in a city near us.
2. The momentum of Tighter Regulation of AI is High
With Facebook scandals and academic acknowledgment of the dangers of not regulating machine learning & AI, there’s more technological, political and global attention on the need to control technology companies and specifically artificial intelligence in a more coordinated and cautious way.
From self-driving cars to autonomous killing machines, AI is about to impact the world in a significant immediate way in 2019 more than ever before.
3. Automated Killing Machines will Become Common
The Chinese Military and The Defense Advanced Research Project Agency (DARPA) will continue their affront on automatic killing machines, where military affairs continue to get a bit more robotic and mechanical.
This impersonalizes national territorial war-fronts possibly making the likes of Russia and China more daring in their military affairs.
These military powers will tell you the race to AI is not just about economic and technological supremacy but global domination.
4. Technical Consolidation as Automation Hits New Wave
In the business and enterprise world, several micro trends will impact how machine learning becomes more mainstream.
These include robotic process automation, Cloud maturity with more in-depth features, improved AI analytics, IoT integration, edge computing, distributed ledger adoption (blockchain), logistics upgrades, automobile industry adoption of autonomous vehicles and a host of things related to AI but more like applications of AI.
These result in more automation hitting the likes of business processes, finance, retail, transportation, healthcare, and education.
5. Smart Speaker is the “AI” device After Mobile
The smart speaker market reached critical mass in 2018, with around 41 percent of U.S. consumers now owning a voice-activated speaker, up from 21.5 percent in 2017, according to TechCrunch.
The penetration of the Voice-AI interface in the smart home means IoT and artificial intelligence have begun their merge and amphibious assault on the consumer. What will this mean?
It will mean $Billions for Alibaba, Amazon, Google, Apple, Samsung, Xiomi, Baidu, and others to develop a new way of relating to consumers and bridging the online to the offline gap.
As personal assistants become more sophisticated, AI-as-a-service becomes much more ubiquitous with a line of convenience beyond mobile and apps looking very probable.
As everything becomes “smart” with Voice-AI integration, we won’t need to push buttons with our thumbs; even that will seem tedious.
This list will grow as we head closer to 2019, so recheck the article if the topic interests you.
6. The Race for AI Chips
There’s a new race for AI chips that are highly specialized. The advent of field gate programmable array (FPGA) processors for specialized tasks like Big Data created a new niche. Technology companies are bypassing the usual chip makers and creating their own.
According to Arstechnica while Intel got into the market with its purchase of startup Nirvana Systems in 2016 and it bought a second company, Movidius, for image processing AI, major tech companies are building their own AI chips. Microsoft is preparing an AI chip for its HoloLens VR/AR headset, and there’s potential for use in other devices. Google has a special AI chip for neural networks called the Tensor Processing Unit, or TPU, which is available for AI apps on the Google Cloud Platform.
Amazon is reportedly working on an AI chip for its Alexa home assistant. Apple is working on an AI processor called the Neural Engine that will power Siri and FaceID. ARM Holdings recently introduced two new processors, the ARM Machine Learning (ML) Processor and ARM Object Detection (OD) Processor. Both specialize in image recognition. IBM is developing a specific AI processor, and the company also licensed NVLink from Nvidia for high-speed data throughput specific to AI and ML.
Suffice to say that Huawei already had their AI chips in 2018, and Alibaba is coming out with theirs in 2019. With NVIDIA’s stock down more than 60%, due to the crypto fallout, there’s definitely change in the winds and AI chips is a big deal heading towards 2020.
In 2019, chip manufacturers such as Intel, NVIDIA, AMD, ARM, and Qualcomm will ship specialized chips that speed up the execution of AI-enabled applications, even as Tech companies build their own.
7. Human Bias in AI Systems
The challenge of tackling human bias in the AI systems we create will be front and center in 2019. In 2018 Bias appears to be the Achilles heel of AI. Until this is corrected, our civilization won’t trust AI fully.
AI takes large data sets as input, distill the essential lessons from those data, and deliver conclusions based on them. However, too often the information is biased in some way, and this will bias the system.
As Babbage would likely affirm, the fault here is with the input data, not the AI algorithms themselves, but even the ethnicity and gender of the software engineers here pays its role. Facebook itself admits it might take years for its AI to be able to recognize misinformation, bad actors, or even hate speech.
We are just starting to uncover biases in the most basic algorithms, and prejudice in all of our systems exists. Better data sets and better training are only part of the problem. I believe this will continue to be a hot issue in 2019.
8. Advances in Neural Networks
To model artificial systems on biological systems has a certain intuitive elegance about it. There’s been some good progress in Neural Networks. Artificial neural networks rely on the idea that technologies can model the biological work of the human brain, using small units corresponding to individual human neurons and groups of neurons, to produce outputs based on inputs.
If the neural network is not an algorithm, but instead a framework & methodology of various machine learning algorithms to come together and produce a system capable of higher level computations; the possibilities here are promising to say the least.
Many vital functions of AI are based on advances of ANNs (artificial neural networks). You can think of natural language processing, which has seen immense evolution in just the last three years. AI training in game playing is another example.
9. AI will be Applied to Healthcare in an Accelerated Way
You don’t have to have followed Google’s Medical Brain developments to realize AI will be applied to healthcare in an accelerated manner in 2019. AI could be at the center of creating a more patient-centric system of care that begins in the smart home in the future.
AI will have access to our electronic medical records (EMR) and be implicated in advances in neuroscience, genetics, cancer diagnosis, early diagnosis systems, and predict patient outcomes successfully helping with drug and pharma R&D. Robotic and automated surgeries will continue to increase, and as big Tech companies become more implicated in healthcare, our health data will be used to augment healthcare with more AI-specific innovation.
Alexa skills already help global citizens deal with chronic diseases and conditions to help family members take care of loved ones. Healthcare is one of the most significant fields, no doubt where the impact of AI will be felt the most in 2019.
10. AI as Augmented Enterprise Toolsets
Explainable AI that can augment the tasks you do, no matter your job. Gartner research indicates that by 2020, “85% of CIOs will be piloting artificial intelligence programs through a combination of buy, build, and outsource efforts. In 2019, AI will automate decision-making in the most efficient way possible.
As the Cloud matures, so do AI tool-kits that allow AI and humans to work together more efficiently. Many machine learning applications don’t currently have a way to “look under the hood” to understand the algorithms or logic behind decisions and recommendations, so this field is sometimes referred to as “explainable AI.” It’s the humanization of AI tools that can easily reach your average enterprise employee, no matter their role or position in your organization. Bringing AI tools to the masses will be a major theme in 2019.
When I chose the cover image for this article, it’s not by accident that I decided Alexa for Business. Natural language humanizing your data at work is one of the significant ways this will occur in 2019.
12. Artificial Intelligence for Social Good
While the American media dramatizes the negatives, there’s a lot of social good coming with AI. Gartner research indicates that “social media mentions of data for good have increased 68% in the last year” as the general public becomes more aware of how data can make a positive impact on society. The world needs AI that benefits humanity more directly and entrepreneurs that care about social entrepreneurship, the sharing economy, social equality, and creating inclusion rather that division.
Whatever this may be, technology and specifically AI will have more narratives of the positive in 2019. The idea that human beings are social and creative creatures that can be freed from repetitive tasks and drudgery will only increase in sentiment in 2019 and moving forward for the better. Also, aspects of how AI can improve analytics on our well-being will be brought to the foreground. We can see with this the mindfulness and meditation apps of years past.
What we are finding is data collaborators amplify and augment good social aspects of AI. Additionally, big tech companies are becoming more involved in corporate social responsibility initiatives. Salesforce and Walmart come to mind. More data, better analytics, and more AI transparency can lead to beneficial social change.