Give data and ask for more in a day
We bid a lot of goodbye to Google, Facebook, Twitter. The question of what we should get out of it is just as important
We say goodbye to Google, Facebook, Twitter. Equally important is the question of what we should get out of it. The question is, what percentage of interest should investors get?
Data Science is a modern-day tool. It is important to think about how these tools are used and what can be achieved using them. Using science, you can find out over and over again what the pattern looks like. A large part of science, machine learning, consists of the various algorithms used in it, aiming to find and predict frequently observed things in science.
What kind of prediction, depends on what questions we ask. Now comes Google’s Smart Compose; When writing an email in English, three words are followed by the next one or two. It predicts what the next words will be. Google and Facebook provide a translation. Right now they’re a little fun; Translating simple sentences is not very difficult for science. We often say goodbye to this work. Google will suggest a fourth word after you enter three words using what you type in Gmail. What’s the next word when you say “there’s a lot of wind today”? There will be lakhs of words in the Marathi language; Only a limited number of words can be found in this sentence. This is a kind of pattern. After Diwali, it becomes easy to decide who is writing an email to their mother, what will be the text, what is the time of year, and who is writing to whom. It’s a different departure, a different pattern. Using such a variety of vids, one guesses what the next word will be.
At least in the next few years, this system will not be able to write properly in ‘Lok Satta’ or ‘Vida-Bhan’. If this is a simple, commonly used sentence, it is easy to guess (!) What will be the fourth word after three words? After giving a complete paragraph it will be possible to write the next sentence. But as predictions start coming out, the accuracy of predictions will decrease. But what exactly to say next? If you’re texting a friend, ask, “Would you like to go for a walk? many other topics come to the fore; It is not easy to predict what you will do next when talking to a particular person.
The second part of science is to suggest change through study. While writing the article, Martini complained about an earlier article, “The article has a very old value-based language. The article contains words like ‘widow’, ‘saubhagya’, ‘kadimod’, ‘mard Maharashtra. ‘Widow, Kadimod means something bad; good luck, everything is fine, and in ‘Mard Maharashtra’ there is no place for modest people or women? Such a notion can be inferred by learning the language of science – “Today The weather is very nice. Good luck!” Or as learned scholars might say – let us study the context in which the language is used.
It matters how much information you have, how many countries you got it from, and what information can be derived from that knowledge, not statistics that are not important beyond numbers, such as the Guinness Book of World Records. If you want to study by departure, it is not so when you receive complete departure. He has to ask important, interesting questions.
The political part of it is completely redundant here. The important point here is to understand where the tweets came from – which hashtags were used using geotagging. It was possible to get information about where the question is being written about Maharashtra. A lot of people write on Twitter, which means Twitter has a lot of discounts available. Until Chaturvedi asked Vida the right question, no information was received from him.
The same goes for Google Trends. Scientists study Google Trends; And predicted a month before the Lok Sabha elections in April. These predictions were much cheaper than other surveys – or too many people spent a bit more on the – electricity, internet connection, etc – and the accuracy of these predictions was very high. A few months before the assembly elections, Sharad Pawar was looking very popular in Google Trends. The transition from NCP to other parties had not even begun at that time; ED notice etc. came later. Although some people were predicting that the NCP would end before the elections, it did not happen. It is possible to predict the election season by carefully studying Google Trends.
We also bid farewell to Twitter, Facebook, Google, and now TikTok. What do you get out of it? (trends.google.com) Using it, people can find what they need and what they think is important. Till the writing of the news, it was not clear who was the Chief Minister of Maharashtra and there was talk that President’s rule would be imposed. Between November 6 and 9, Google spread about President’s rule from Maharashtra; Average of last seven days
Language is the language used by reputable technology companies that make linguistic models. That language is slightly inclined to discriminate inequality in society. Models created using racist, racist, bigoted, monotonous writing help spread the same kind of deadly discrimination and harm (society). An article about some of the important records in this research.
Think about how the hieroglyphics feel. “Some researchers, engineers, male writers, and male doctors were sitting at the table in the corner. The idea was to write a sci-fi story together. Everyone is good at their job. And they all wanted to work together. ”
No one is in the habit of reading ERV male writers and male doctors. The English language is no exception. (There are very few exceptions to this kind of language use.) To give a slightly different example, in Marathi we use only one word ‘gay’, in English there are two words ‘lesbian’ and ‘gay’. Publications that do not generally consider homosexuals to be the same human beings use the word ‘homosexual’. The term ‘woman pilot’, ‘woman scientist’, or similar terms are common in Indian English. Even in the liberal media, by writing like this, these businessmen are being made happy and there is nothing wrong with it, no one feels special.
On the other hand, you may have seen horrible translations on Google, Facebook. It was recently reported that BJP MP Raksha Khadse’s constituency is homosexual; And so it was written on the BJP’s own institution. This was a terrible scholarly translation of the constituency ‘Raver’. Since Raver is basically the name of a village and a constituency, the translation of that word would be Raver, this is the first linguistic mistake. Besides, Raver is not homosexual, this is another.
People translate, but there are some differences between good translations. Even when people translate, it seems to be humorous. This is often the case in Marathi advertisements. But those jokes are different from jokes made by artificial intelligence. The reasons behind the horrible humorous translations made by human beings can be found if one thinks about it, but the reasons for the humorous translations made by artificial intelligence are not easily understood. This is the point of Tinmit Gebru, Emily Bender, Prabhu.
Just as decision trees are neural networks, so are many other Tractor models used in science. Of these, the issue of how good the prediction is often important; But when an applicant wants to approve a loan or credit card (no), it is also necessary to explain why he made the prediction; Neural networks are never used in such places; It is difficult to explain them. Sometimes the release is too much (big data), sometimes too little. It takes a long time to make some kind of model, And we need an immediate answer.
Just look at the examples above; It takes at least two hours to diagnose cancer, But the point of the email is that spam has to be fixed in a matter of microseconds. When you google, one or two words are typed and ten predictions of what the next words will look like are shown in a jiffy. These decisions have to be made very quickly, even when driving an automated vehicle. Many decisions have to be made whether there is a person in front of the vehicle, whether there is a vehicle, whether the signal is green, whether the vehicle is in the lane.
At the root of all this are statistics, mathematics, and computer science. Until the commercial use of science, artificial intelligence (AI) was not possible, it was limited to university research. This technology is far removed from all of our, ordinary lives. Now, what do you see in emails, on Facebook-Twitter, what chemicals are used to make medicines from here, the diagnosis of cancer is made before the doctor’s eyes; From emails to cancer and consequently, science has to do with our privacy, our values, our morals, our copy of life.
