Modern artificial intelligence can find corresponding patterns, then classify objects, make decisions, and evaluate the results. It can use feedback loops to learn and adapt to new situations. Gerststein believes that the entire cycle may take years in large organizations, but a well-designed process driven by artificial intelligence can be completed within a few days. It can recode itself, deduce changes, and verify that it is actually moving in the direction you want-all of which is done with accuracy and speed beyond human capabilities. This is quite powerful. But it is also quite threatening.
The more data an artificial intelligence system has, the faster its capabilities will improve. However, for some companies and organizations that have less data, how to meet the data needs of artificial intelligence is a difficult problem. However, this does not mean that such companies and organizations cannot use artificial intelligence. In 2020, more artificial intelligence systems will rely on "neural symbol" technology that integrates learning capabilities and logic. Neural symbol technology is the key to breakthrough natural language processing technology. It can combine common-sense reasoning and professional knowledge in various fields to help computers better understand human language and dialogue. Such breakthroughs will help companies deploy automated customer care tools and technical support tools with stronger dialogue capabilities, and will also greatly reduce the amount of data required to train artificial intelligence.
We still know little about the challenges that artificial intelligence may bring, and serious public discussions are still lacking. The public's imagination of artificial intelligence is still dominated by science fiction and film and television works to a large extent, and there is a lack of awareness and concern about the possible impact of artificial intelligence in the future. At the policy level, the focus on artificial intelligence is still largely focused on the technical and economic levels, and there is a lack of overall thinking and discussion. Although a few scholars in the fields of philosophy and social sciences have begun to pay attention to the ethical issues and social challenges brought about by artificial intelligence, these discussions have not entered the field of public policy, and the focus of the discussions has mostly focused on topics that are still relatively remote such as super artificial intelligence. on.
The goal is to be acceptable to the executor and can be accomplished through hard work. When arranging work tasks at a higher level, you must first make some measurement yourself to see if the standards for achieving your goals can be achieved. If you have a little difficulty, it’s okay. Try hard. If you have a certain degree of difficulty, you have to ask your superiors if you can and will provide certain resources for support. If so, that’s acceptable; if the degree of difficulty is too high, You should learn to say no. After all, goals should be jointly formulated.
In summary, the goal is to be acceptable to the executor and can be accomplished through hard work. When arranging work tasks at a higher level, you must first do some measurement yourself to see if the standards for achieving your goals can be achieved. If you have a little difficulty, it’s okay. Try hard. If you have a certain degree of difficulty, you have to ask your superiors if you can and will provide certain resources for support. If so, that’s acceptable; if the degree of difficulty is too high, You should learn to say no. After all, goals should be jointly formulated.