Latest AI Trends to follow in 2019

Artificial Intelligence (AI) is a revolutionary technology that is changing the world. It will not decline and it will continue to grow. According to a Deloitte study, “82% of companies that have already invested in AI have gained a financial return on their investment.” AI is being integrated into recording pen and spy glasses. AI also continues to transform lives and business. Artificial Intelligence enhances products and it makes businesses to be optimized as better decisions are made.

Latest AI Trends

1. Reinforcement learning: This is a framework that makes use of sequential decision-making that is driven by experience. This method moves towards a goal by interacting with the environment. Reinforcement learning is used by many game playing algorithms.

Reinforcement learning continues to grow as many industries are experimenting with it. Industrial cases of reinforcement learning include:

a. Healthcare: Reinforcement learning helps to determine treatment policies for illnesses such as diabetes, schizophrenia etc.

b. Finance: Reinforcement learning such as the LOXM RL program by JPMorgan Chase helps to execute trade in the stock market and it also increases the speed by which client orders are executed.

c. Higher education: Reinforcement learning is use to personalize teaching and learning systems.

2. Ethics in Artificial Intelligence: According to IEEE global initiative on ethics there has to be policies or standards around AI that focus on:

a. Transparency: This will reinforce data usage, audit trails and access to rules that are in the system.

b. Accountability: It is important to know if legal responsibility or property law will deal with any harm caused by AI systems

c. Governance frameworks: There has to be processes, procedures and standards that do not infringe on human rights.

d. Policies: There has to be policies that deal with the impact and implications of AI.

e. The social and legal impact of AI is growing. A fatal incident that involved an autonomous car raised questions of who was responsible.

Most in the public are skeptical about AI and its application and the issues of transparency of AI’s will continually rise as AI is applied in different industries.  A trustworthy AI must respect human rights, principles, values and it should be reliable. 2019 will see an increase in privacy conversations. Most people are unaware of how their data is being used and Facebook’s recent crisis has increased the call for privacy.

3. Convergence of AI: A trend of AI in 2019 is the convergence of Artificial Intelligence with Blockchain and Artificial Intelligence with Internet of Things (IoT). Self-driving cars will not be possible if IoT was not working closely with AI. IoT help self-driving cars to collect real time data and the programs used for decision making in self driving cars is powered by AI models. AI algorithms can take actions and make decisions by using data. They can also engage in path planning, natural language processing and eye-tracking that will help improve driver monitoring. AI’s utility in IoT applications will increase in 2019 as there is increased functional ability in predictions and analysis.

AI combines with Blockchain to improve security, scalability, privacy and customer trust.

4. Quantum computing: Quantum computer use quantum bits (qubits) to store information and this makes computation to be faster. In 2019, quantum computers seek ways to reduce error rates. According to “Andrew Childs, “Current error rates significantly limit the lengths of computations that can be performed, we’ll have to do a lot better if we want to do something interesting.” With quantum computers; problems that seem insurmountable can be solved.

5. Biased data: There will be more and better ways to deal with biased data in 2019. Businesses are taking steps to adopt principles that focus on non-discriminatory data. Ways to prevent of reduce discriminatory outcomes in machine learning include transparency, the active inclusion that arises from the diversity of inputs and the review of risks.

6. Facial recognition: 2019 will see an increase in the usage of accurate and reliable facial recognition technology. Facial recognition technology can help in law enforcement, payment processing, shopping, advertising and biometric identification. Facial recognition technology includes China’s SenseTime and Facebook Deepface.

7. Automated machine learning: Automated machine learning (AutoML) will allow complex problems to be solved with the creation of specific models. It will allow developers and programmers to only focus on problems and not on the workflow and entire process.

8. Chatbots: More businesses will adopt chatbots in 2019 as chatbots are available 24/7, they can help customers check out, they are good at forwarding conversations to the appropriate employee, they are good at emergency responses and placing orders.

9. Voice search: Voice search has grown in popularity as more individuals use it on daily basis. According to Comscore, half of all internet searches will soon be via voice search. Examples of voice search include Siri, Google Assistant and Cortana. More people are projected to use speech recognition in 2019 as many businesses are adopting AI.

10. AI chipsets: Chip manufacturers like NVIdia, Intel, Qualcomm, AMD and ARM are making chips that will enhance the execution speed of AI-based apps. More research and development into chips will move AI further into the automotive and healthcare sector.

11. Neural networks: This emulates the brain and they store data in digital formats. There is a growing demand of neural networks that will help improve prediction in artificial intelligence. AI will become more sophisticated with the addition of neural networks as they help in deep learning.

12. Deep learning: Deep learning helps in voice control, images recognition and self-driving cars. An example of deep learning in Amazon’s Alexa natural language processing algorithms.

13. Deep learning:  The number of jobs that require deep learning has increased over time as deep learning continues to be applied in many areas of artificial intelligence.

14. Cybersecurity: The application of AI will empower and make cybersecurity to be more robust. Cybersecurity will be able to efficiently monitor threats and vulnerabilities.

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