Artificial intelligence has been a dream of mankind for decades. Many have claimed that AI is just around the corner, but those claims have been unsubstantiated. There was no true progress made on developing and implementing the technology required to make artificial intelligence possible until recent years. Now, many startups and large corporations are vying to become market leaders in this exciting field.
Although we’re still several years away from seeing widespread adoption of AI systems, we can look at existing solutions and projects (most of which are currently limited to research labs) as indicators for what’s coming next. Here’s an overview of some top trends:
#1 – Deep Learning Will Continue To Grow and Improve
Deep learning is by far the most exciting field in artificial intelligence, with the biggest leaps in recent years. Neural networks that are modeled after biological systems (deep learning) have allowed computers to achieve things like voice and facial recognition, which were previously only possible through decades of programming. Artificial neural networks learn similarly to how humans do. The difference is that while humans can learn anything given enough time and information, AIs need huge amounts of data to work effectively. To improve deep learning models requires significant computational power, but computing hardware is becoming cheaper and more powerful every year.
Monte Carlo Tree Search (MCTS), a popular game-playing AI technique developed by Rémi Coulom in 2005, uses Monte Carlo methods to choose promising moves when playing a game. Deep Mind used a combination of MCTS and deep learning to create AlphaGo, which defeated the world champion in the ancient Chinese board game Go. So far, most advancement has been made using games as a testing platform due to their ability to generate large datasets and competition between AIs. But as computing power continues to advance, we’ll see AI move past games and into other sectors such as business intelligence or autonomous vehicles.
#2 – AI Will Help Us Discover New Drugs and Improve Clinical Trials
The pharmaceutical industry is worth an estimated $425 billion per year, yet it faces serious challenges: each new treatment currently goes through laborious clinical trials that often take over 10 years and cost $1.3 billion per approved drug and 90% of potential treatments never make it out of the lab. AI can help us reduce these timelines and costs by accelerating drug discovery, allowing pharmaceutical companies to identify effective drugs more frequently through data analysis. Pharmaceutical companies are already using AI for tasks including early detection of efficacy issues with experimental drugs in clinical trials, which helps prevent millions in losses per year. As the field of AI matures, we’ll see an increasing number of tech giants investing in areas such as medical imaging where they have “insurmountable expertise”. We could also expect to see major players purchase smaller biotech firms that specialize in personalized medicine or genomics, which would be a huge step forward for healthcare research.
#3 – The Rise of Chatbots And Assistants
Consumer expectations have skyrocketed in recent years. People have grown accustomed to near-perfect user experiences, so it’s no wonder that there has been a massive shift towards chatbots and AI assistants for customer service roles. In the future, we’ll see more of these bots being automated through deep learning. Bots will learn from previous interactions with customers and get better at assisting over time, giving users a personalized experience while supporting businesses’ bottom line by reducing costs and improving operational efficiency. Another great application of chatbots is in the medical field where they can provide 24/7 help to patients who are unable to see a doctor due to high costs or long wait times. Bots could be used to triage patient concerns, check their symptoms against known conditions, and decide whether an appointment with a doctor is necessary or not. They would also be able to tell users when they should seek professional advice, referring them to appropriate resources if needed.
#4 – Agents Will Become More Like Humans And Change Our Lives For The Better
So far all AIs have been limited in some way: Watson can answer questions better than any human but often requires multiple systems to work together; Google Now can give you information before you even search but doesn’t understand relationships between objects; even Alpha Go has to trade-off between speed and accuracy when playing Go. Eventually, AI will be able to act like humans in every capacity, with the potential to solve many of humanity’s biggest challenges. This could lead to massive progress in science, engineering, technology, and other fields that require creativity or abstract thinking. “Super intelligence” is an area of active research at the moment, where scientists are studying how we can ensure that any future super intelligent systems have values aligned with ours so they don’t pose a threat to humanity. There are also ethical concerns around artificial intelligence that need serious consideration before it becomes mainstream.
#5 – Expert Predictions about How AI Will Affect Jobs and The Economy
The World Economic Forum (WEF) surveyed nearly 800 experts on their predictions about how AI will affect the global economy over time. 70% of those polled were concerned that there would be a widening gap between rich and poor as talented workers compete with machines for high-paying jobs, while 60% believe that companies will be able to reduce employment levels through improved automation. There’s no need to panic, however. The WEF also polled the same experts on whether or not technology will displace more jobs than it creates, with 83% saying that tech would create more jobs than it destroys. This has happened throughout history and is likely to continue in the future.
Conclusion:
The AI revolution is just beginning, and we’re still in the early stages of understanding how it will affect our everyday lives. Physicist Stephen Hawking recently said that “the real risk with AI isn’t malice but competence,” so let’s hope we can figure out these issues before any major problems arise. We’ll also see a greater diversity of industries adopting AI over time through personalized medicine, online shopping, cyber security – even agriculture. As the cost of computing continues to fall and capabilities expand, we should expect to see widespread adoption of machine learning in nearly every industry in some form.
Author Bio:
Sarah has been writing for a decade and now for the Quran teacher near me Website. She obtained her Master’s degree at the University of London. Her main objective is to write insightful content for those people who read and like it.
