Training HailyAI To Care About Your Business

HailyAI cares about business
Training HailyAI to care about your business! As discussed in our previous news releases on training HailyAI (View previous post), we’re continuing to make progress on refining HailyAI’s writing capabilities.  One interesting finding of our training is that by balancing our training articles towards business topics, GPT-J picks up on that and will look for ways to relate article topics to marketing/commerce/etc. topics.  Our customers are focused on those niches, so this is a good target for our initial Satellite Blogger launch.  We’ll of course further train it for handing a wide variety of niches going forward.
See below for a good example of this!  We asked HailyAI to define AI NLP models.  She did indeed describe the technologies between it in the introduction of her article.  The cool part though is she interpreted this as the start of an article about using NLP models for business, and explained the challenges you’d face as a company trying to adapt it.
Headline: What are AI NLP Models?

By: HailyAI

Artificial Intelligence (AI) is a broad term that encompasses machine learning, natural language processing and deep learning.

Machine Learning is the ability of computers to learn without being explicitly programmed. It’s how Facebook and Google categorize content. Machine learning algorithms can be trained to recognize patterns in data and make predictions based on those patterns.

Natural Language Processing (NLP) is the ability for computers to understand human language.

This includes text mining, information extraction and summarization.

Deep Learning is an advanced form of machine learning. Deep learning is used to create computer programs that mimic the way humans think. These programs are able to perform complex tasks such as image recognition and speech synthesis.

As with any new technology, there are challenges associated with using AI. In this case, it’s the need to train these systems with large amounts of data. As a result, you must have access to a lot of data or pay someone else to do it for you.

In today’s digital world, we’re all data miners. We collect information from every source possible. The challenge is making sense of the data and turning it into useful insights.

The reality is that most businesses don’t have the resources to build their own AI models. They turn to third party vendors who specialize in building AI solutions.

Here are five reasons why your business needs AI NLP models.

  1. To improve customer experience. Customer service has been around since the beginning of time. But in today’s connected world, customers expect 24/7 availability. To meet this expectation, companies must automate processes so they can handle more requests.
  2. To increase sales by providing better product recommendations. Recommendation engines help consumers find products they want. For example, Amazon uses recommendation engines to show customers other items they may like.
  3. To enhance search results. Search optimization helps people find what they’re looking for when they type keywords into a search box. In today’s connected world, search engines must be able to answer questions quickly and accurately.
  4. To provide targeted marketing messages. Marketing automation allows marketers to send tailored communications to prospects and customers. By contrast, broadcast media requires reaching everyone at once.
  5. To streamline internal processes. Internal processes are often manual and require lots of back-and-forth between employees. Automating these processes frees up employees to focus on higher value work.

While many organizations use some form of AI to process massive amounts of data, they still need to hire staff to analyze the information and determine actionable insights.

If your organization is considering adding AI to its offering, here are three factors to consider.

  • Data quality – You must ensure that the data you’re feeding into the AI model is clean and free of errors. If the data isn’t accurate, the AI won’t function properly.
  • Skill set. – Trained to understand the nuances of the problem domain. Otherwise, the AI will be unable to extract relevant information from the data.
  • Time. – Building an AI solution takes time. Therefore, you must plan for sufficient resources to support the project.
With the increased usage of AI across industries, it’s critical to assess whether you need to add this capability to your offering.
#ai #startup #nlp #blog #aitools

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