Inser LinkedIn’s AI Releal: Search Fobs Bayshod LLM distillation

Encourage the emergence of research in the natural language people to change how to search for information, and LinkedInThat was Work with many artificial intelligence models During the past year, this shift hopes to search for a job.

The search for jobs on behalf of LinkedIn, now available to all LinkedIn users, is used as distilled models on the basis that have been trained on the basis of knowledge of the professional social media platform to narrow possible job opportunities on the basis of natural language.

“This new search experience allows members to describe their goals with their own words and get results that really reflect what they are looking for,” Iran, Berger, Vinturebeat, Venturebeat, told Venturebeat in an email. “This is the first step on a larger trip to make the search for work more easy, comprehensive and empowering for everyone.”

LinkedIn has already mentioned in Blog mail There is a big problem that users faced when searching for functions on the platform was excessive dependence on microscopic keywords. Often, users write more general job ownership and get functions that do not fully match. From the personal experience, if you write a “correspondent” on LinkedIn, get search results for the correspondent jobs in media publications, along with the correspondent of the court, which is a set of completely different skills.

Vice President LinkedIn Engineering told Venturebeat in a separate interview that they saw the need to improve how jobs are fully suitable, and began to understand better what they were looking for.

“In the past, when we use keywords, we mainly look at a major word and try to find accurate matching. Sometimes in a job description, the correspondent job description may say, but they are not a truly correspondent; we still recover this information, and it is not perfect for the candidate,” said Zhang.

LinkedIn has improved her understanding of user information and now allows people to use more than just major words. Instead of searching for a “software engineer”, they can ask, “finding software engineering functions in the Silicon Valley were recently published.”

How did they build that?

One of the first things that LinkedIn had to do is to fix the ability of the search job to understand.

“The first stage is when you write a query, we need to be able to understand the query, then the next step is that you need to recover the appropriate type of information from our job library. Then the last step is that you now have like a hundred final candidates, and how you do the arrangement so that the most relevant function appears on top,” Zang said.

LinkedIn relied on the classified styles based on classification, arrangement models, and the oldest LLMS, which said “lacked the ability to deep semantic understanding.” After that, the company turned into a more modern and ablution large language (LLMS) to help enhance the capabilities of natural language processing (NLP).

But LLMS also comes with expensive account costs. Therefore, LinkedIn turns into distillation methods to reduce the cost of using expensive graphics processing units. They divided LLM into two steps: one to work on retrieving data and information and the other to classify the results. Using a teacher model to classify query and function, LinkedIn said he is able to align all of the recovery and classification models.

The method also allowed LinkedIn to reduce the stages used by a job search system. At one point, “there were nine different stages that form the pipeline to search for a job and match”, which are often repeated.

“To do this, we use a common technique for multi -targets.

LinkedIn also developed a query engine that generates dedicated suggestions for users.

More based on artificial intelligence

LinkedIn is not alone in seeing the possibility Llm -based institution search. Google He claims this 2025 will be the year When Search Enterprise becomes more powerful, thanks to advanced models.

Examples like cohereHelp 3.5 helps Break the language of the language Inside companies. various “Deep Search” products from Openaiand Google and man It indicates the increasing regulatory demand for agents who reach and analyze internal data sources.

LinkedIn has been offered many features of artificial intelligence last year. In October, it was launched Amnesty International Assistant to help recruits Find the best candidates.

Deepak Agharwal, chief artificial intelligence employee at LinkedIn, will discuss the company’s artificial intelligence initiatives, including how to expand the employment assistant from the initial model to productionduring Vb converting in San Francisco this month. Register now to attend.

Daily visions about business use cases with VB daily

If you want to persuade your boss at work, you have covered VB Daily. We give you the internal journalistic precedence over what companies do with obstetric artificial intelligence, from organizational transformations to practical publishing operations, so that you can share visions of the maximum return on investment.

Read with us privacy policy

Thanks for subscribing. Check more VB news bulletins here.

An error occurred.