Many venture capital firms and investors are now turning to artificial intelligence and data science to help them make wiser decisions. This is helped by the fact that machine learning and artificial intelligence have matured to such a level that they can help corporations make useful decisions. For example, Google was able to increase the accuracy of its rankings by manufacturing its own AI processing Chip technology named TPU. Many other companies are following suit, and they are figuring out how useful machine learning and artificial intelligence can be in making decisions. In the financial industry, these firms are starting to see how using data and machine learning algorithms can increase the success they have with their decision-making. They can build AI models to predict how their investments will go, and they can also rely on historical data to help their algorithms be more accurate.
The Increase In Computing Power Has Made It Easier
Before tech investors had such access to increased computer power to the cloud, there were making decisions based on modeling and high-frequency trading. Today, the cloud has made it possible for them to lean on machine learning models, and it is improving the decision-making process for them. They find that they can make better decisions using the monumental amount of data currently being outputted in the industry. They are using modern information processing algorithms to feed their machine learning models, which is further making their decisions more accurate. It is leading to a massive speedup in the way they work and make decisions.
The Software Stack Is Maturing
One factor making it easier for investors is that they are now more software than ever for machine learning. The Python programming language has many libraries, such as NumPy and SciPy. There are also libraries like Tensorflow from Google. These software solutions are making the barrier to entry much lower, and it is making it possible for corporations to start incorporating these tools into their workflow. On top of that, cloud computing has made storage quite cheap so that companies can host terabytes of data relatively cheaply. They also don’t need to worry about infrastructure, as most of it is not taken care of by software tools like Kubernetes.
The Competition Is Using It
One of the main factors influencing this is the fact that financial institutions are all using it. If a financial institution gains value for machine learning and artificial intelligence, its competitors will have to start using it too. This is because the competitors need some way of keeping pace, and using the same software stack to gain better accuracy is a great way of doing that. As competition heats up, it will only get more important for corporations to go all out in incorporating machine learning and artificial intelligence into their stack and workflow.
The Technology Will Only Get Better
The biggest reason financial institutions are adopting more artificial intelligence and data science is that these technologies will only get better in the future. Algorithms are improving, and the computer power from things like graphics processing units is getting better. This will lead to a world where artificial intelligence models will be produced more quickly and readily. It will lead to a speedup in how quickly companies can go through the process of using machine learning models to improve their results in the financial industry.