Post by gracie22 on Mar 28, 2024 12:51:59 GMT 1
This is due to the abundance of image models. Another area in which this technology has been applied with very good results, and where recent advances (about ten years) have been spectacular, is that of speech recognition and machine translation, for example. It’s not perfect yet, but it works much better than in the past, you just have to somehow feed the system with data. What other positive implications of AI can we envision for the near future ? I believe very strongly in the application of machine learning and deep learning in the field of medicine, which is a field where we have a lot of data to exploit.
Let’s take DNA as an Portugal Phone Number List example, it’s statistically very interesting because of the huge mass of data sequences. We can imagine that with these AI technologies, we will be able to recover all the data from sick or healthy humans and create models to know if we observe or mutations, even before they happen. There is also visual medical imaging. We can apply what we have done to a range of activities, from recognising the images of animals to diagnosing breast cancer, for example. Millions of different breast cancer images can be provided to a machine, well labelled by doctors or not, and this machine will necessarily know much more than any doctor, no matter how learned he or she has ever been.
These machines will be extraordinary helpers. How evern they will probably remain as such, because AI is just a tool. Ultimately, it is human beings who can control what a system does. Then, let’s take autonomous cars. From the statistical data generated by cars while driving, we can imagine that they can increasingly react by themselves in cases where speed is crucial and humans would not have reached the necessary speed. So, these visual sensors (by radar or lidars or cameras) are also image recognition systems that will increase the vehicle range. However, I personally do not think that with the current statistical techniques, a car can be 100% autonomous (level 5 as specialists say).
Let’s take DNA as an Portugal Phone Number List example, it’s statistically very interesting because of the huge mass of data sequences. We can imagine that with these AI technologies, we will be able to recover all the data from sick or healthy humans and create models to know if we observe or mutations, even before they happen. There is also visual medical imaging. We can apply what we have done to a range of activities, from recognising the images of animals to diagnosing breast cancer, for example. Millions of different breast cancer images can be provided to a machine, well labelled by doctors or not, and this machine will necessarily know much more than any doctor, no matter how learned he or she has ever been.
These machines will be extraordinary helpers. How evern they will probably remain as such, because AI is just a tool. Ultimately, it is human beings who can control what a system does. Then, let’s take autonomous cars. From the statistical data generated by cars while driving, we can imagine that they can increasingly react by themselves in cases where speed is crucial and humans would not have reached the necessary speed. So, these visual sensors (by radar or lidars or cameras) are also image recognition systems that will increase the vehicle range. However, I personally do not think that with the current statistical techniques, a car can be 100% autonomous (level 5 as specialists say).