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The author is To find the Stanford Author Institute of AI focused on AI
The physical intelligence advances at the speed of breaking. The most used to take models to make roads can be done in minutes, and while training costs are very high, they will arrive as developers to learn to do more. I said it before, and I will repeat it – in a ai future now.
And who is in the field, this is not surprising. Computer scientists were difficult at work; Companies have appeared for years. A horror – and the raising of the eyes – is not the absence of non-ai. Yes, AI is progressing quickly – and it is necessary to ensure that everyone is helpful.
As a technician and teacher, I feel the strongest to each of us in the AI's system is responsible for advance and confirming the concept. It is hard work, requiring a set of guidelines. In preparation for a AI's action conference next week in Paris, I placed three important principles in the ai.
First, apply science, not a science fable. Scientific work base is to depend on data data and strict research. The same system should be used in the control of AI. While the condition of the future has installed our thinking – even if the Utopia or Apopia or Apocalypse-promibition system requires a clear idea of the real thing.
We have made progress in places such as image check and correction. The software software relief programs are turning work on interesting ways – but use the DEPPERCLE for reading and reading. They are not mental types of minds, free will or mind. Understanding this is important, saving us from distasteous conditions, and he allows us to pay attention to important challenges.
Due to the difficulty of AI, they even focus on our truth is not always easy. Adding a gap between science and real requests, we need tools that will share the correct and formal information about its skills. Institutions, such as the US National Institution and Technology, can enhance the world's world outcomes, which lead to the policies offered, collected.
Second, have a pragmatic, instead of the idea. Without progressing progress, a Ai field is still in the fringe, which contributes to their priority. If so, policies about what you can build and cannot be built and reduce the unexpected results while working unexpected while enhanced.
Take, for example, the use of ai to diagnose the disease. This can be comfortable immediately to reach the highest medical care. Yet, if it is not wellbered, it can expand biases in today's health systems.
To develop ai is not an easy thing. It is possible to develop a model for the main purpose, and that is the model used later. The best administrative policy, as a result, will be created by reducing risk while you reward the implementation of the responsibilities. Policy developers should be a reduced payment policy for the use of misconduct for the use of purpose without improper.
Finally, empower ecosystem. The technology may encourage students, help to care for our elderly and solid cleaning skills – and the most important things are in work. It is all important that the policymakers equip everything ecosysystem – including open and education community.
Open to AI models and computer equipment is important for progress. The flow will make the obstacles and productivity, especially educational institutions and researchers have fewer areas than overstor. The result of the limitations, of course, increased beyond Alfriend. If present-day science students cannot investigate the best way, they will not understand this process when entering a private sector or decide to receive their companies – their gaps.
AI change is available – and pleased. We can improve our global environment in Ai-Rown Genea for AI, to work, we need available control, cooperation and deep drop in high-cost values.