Whilst I have been following AI now for a good few years now the pace is starting to hot up. I thought to simply recap on the year as a succinct way of sharing tech dev.
Here is a little recap of events in 2019;-
In 2019 advances were made in areas such as natural language processing, computer vision, and robotics, and new applications for AI were discovered across a wide range of industries. Here are some of the key events in AI in 2019.
GPT-2: In February 2019, OpenAI released a new language model called GPT-2, which demonstrated remarkable ability to generate coherent and realistic text. However, due to concerns about the potential misuse of the technology, OpenAI initially only released a smaller version of the model. Later in the year, the full version was made available, along with a tool to detect whether text was generated by GPT-2.
AlphaStar: In January 2019, Google's DeepMind announced that its AI system, AlphaStar, had beaten human professional players at the popular strategy game StarCraft II. This was a significant achievement for AI, as StarCraft II is a complex game that requires strategic planning, resource management, and real-time decision-making.
AI in healthcare: AI continued to make inroads in healthcare in 2019, with researchers developing new AI tools for disease diagnosis, drug discovery, and personalized medicine. For example, a team at Stanford University developed an AI system that can diagnose skin cancer with the same accuracy as dermatologists.
Autonomous vehicles: In 2019, the race to develop autonomous vehicles continued, with several companies testing their self-driving cars on public roads. However, there were also setbacks, including a fatal accident involving an autonomous vehicle operated by Uber in March.
Ethics and AI: As AI technology becomes more powerful, there is growing concern about its potential impact on society. In 2019, several high-profile events highlighted the need for ethical considerations in the development and deployment of AI. For example, Google faced criticism from employees and outside groups over its involvement in a US military project that used AI for drone targeting.
Quantum computing: While still in its early stages, quantum computing has the potential to revolutionize many areas of science and technology, including AI. In 2019, Google announced that it had achieved "quantum supremacy," meaning that its quantum computer had solved a problem that would be practically impossible for a classical computer.
Deep learning: Deep learning is a type of AI that involves training neural networks on large datasets. In 2019, researchers made significant advances in deep learning, developing new architectures and algorithms that improved the accuracy and efficiency of AI systems. For example, Google introduced a new neural network architecture called BERT, which can generate more accurate responses to natural language queries.
AI and climate change: With concerns growing about the impact of climate change, researchers are exploring ways in which AI can be used to address environmental challenges. In 2019, a team at Stanford University used machine learning to develop a model that can predict the impact of melting glaciers on sea levels.
So in reality 2019 was a year of good progress and innovation. Advancements were made in areas such as natural language processing, computer vision, and robotics, and new applications for AI were discovered across a wide range of industries. Nonetheless there is growing concern about its potential impact on society and the need for ethical considerations in its development and deployment.
