[Xinzhiyuan Guide] Ancient literati, or chant and chant, narrate quiet feelings, or wind and dance, chant and return. "Reciting Poems and Composing Pairs" became their standard. Just now, the world's largest artificial intelligence massive model "Source 1.0" was released.

Science students may have nothing to do with liberal arts students when they start to literary.

Do not believe? Look at this seven-character poem:

Although it is not the toad palace banished to immortal, why be afraid of the cold to the bones of the ice palace.

Peeping curtain squinted at Jinwu Xiao, how many talents are here.

After reading it, I have to say that it is really good beer! The connotation of artistic conception is very good.

Not only can write poems, but also write words, such as the following:

I suspected that there were tears in nine days,

Sprinkle it for me.

Drip into the water of West Lake,

Wet the moonlight a thousand miles away,

Turned into the cloud in my dream.

Can you imagine that this is a masterpiece of a science and engineering student who does not know how to write poetry at all?

It is true. Just let Li Bai readers will be silent, let Du readers will be tears .

This is the world's largest artificial intelligence massive model just released by Inspur, called "Source 1.0".

In addition to being able to compose poems, it can also write dialogues, write couplets, generate news, continue writing stories...

With 245.7 billion parameters , the world's largest artificial intelligence model has read 200 billion words.

You know, there is no way to read so many words in a person's life.

Since it is called the largest in the world, how big is it?

The world's largest artificial intelligence massive model!

The title of the world's largest is not a joke!

"Source 1.0" has achieved ultra-large scale and huge quantification in terms of algorithms, data, or computing power.

In terms of algorithms, compared to the English language model GPT-3 with 175 billion parameters, "Source 1.0" contains a total of 245.7 billion parameters, which is 1.404 times the amount of the former .

Moreover, the most important thing is that "Source 1.0" is a single model like GPT-3, instead of being piled up by many small models. In this aspect alone, "Source 1.0" can rank as the world's largest natural language understanding model.

In terms of data, "Source 1.0" has almost "read" all the vast contents of the entire Chinese Internet in the past five years . Through the self-developed text classification model, a 5TB high-quality Chinese data set was obtained , which is nearly 10 times ahead of the training data set size.

In addition, "Source 1.0" has read about 200 million words . what is this concept?

If a person can read ten books a month, a hundred books a year, and 50 years of reading, he will read 5,000 books in his lifetime. If a book is 200,000 words, it will only add up to 1 billion words, and it will take 10,000 years to read. Over 200 billion words . With the support of such a large-scale data, the data set of "Source 1.0" has naturally become the world's largest high-quality Chinese data set.

In terms of computing power, "Source 1.0" consumes a total of about 4095PD (PetaFlop/s-day) . Compared with GPT-3 consumes 3640PD calculations to obtain 175 billion parameters, the calculation efficiency is greatly improved. If you let "Source 1.0" "read" 24 hours a day, it only takes 16 days to read almost all the contents of the Chinese Internet in the past five years .

Um? Have you learned all the Chinese Internet content for the past 5 years?

u1s1, "source 1.0" yyds!

What are the results?

Is it fun to experience the "Turing Test" for yourself? Don't worry, there are still many questions waiting for you!

Now let's take a look at the most powerful imitation ability of "Source 1.0". That is, for a "word" that does not exist at all, only one use case is needed, "Source 1.0" can learn the usage of this "word".

Seeing these familiar "words" do you feel that smell (doge) ? Suddenly I was looking forward to it. If "Source 1.0" learns how to use the word "The clown is myself" , hehe.

Now that the Turing test is mentioned, let's take a look at the results of the test.

"Source 1.0" achieved an average false positive rate of up to 50.84% in the test !

The Turing test adopts the "question" and "answer" modes, that is, the observer controls the typewriter to talk to two test subjects, one of which is a human and the other is a machine. The observer keeps asking various questions to distinguish whether the answerer is a human or a machine.

It is generally believed that after multiple tests, if the machine makes each participant make more than 30% misjudgments, then the machine has passed the test and is considered to have human intelligence.

In the test result of "Source 1.0", the average discrimination correct rate of the respondents was 49.16%, which means the average false positive rate was 50.84%. In the field of news generation, the misjudgment rate is as high as 57.88%.

Among them, the correct rate refers to the proportion of the text generated by the machine can be correctly recognized. The correct rate is less than 70%, which means that the false positive rate is more than 30%.

The data looks too monotonous? fine! The "real questions" session that everyone is looking forward to is here!