AI Exosphere’s Trained HailyAI Writes Better Articles

HailyAI Better Writer
As discussed in our news update, AI Exosphere has been hard at work training GPT-J to be a superior writer.  Out of the box, GPT-J has an impressive knowledge base (courtesy of The Pile which EleutherAI created for its original training, which covers a variety of technological, cultural, historical, etc. sources).   Unfortunately, its writing capabilities are hit and miss.  It does well at short blurbs but doesn’t hold the thread together for longer articles, which Satellite Blogger requires in order to deliver good 1500 word content.
To address these shortcomings, we’re creating a dataset of carefully curated articles which we then use to fine-tune GPT-J.  These articles show GPT-J how to handle longer article, while it maintains its impressive knowledge base so that it can still write about many topics.  Don’t just take our word for it though, check out this sample from HailyAI!  We asked her to write specifically about how to train an AI, which she (correctly) interpreted as a challenge for modern businesses.
Headline:  How Do You Train an AI? (short form article)

By: HailyAI

In the past, we’ve talked about how to train a machine learning algorithm. But what do you do when you have a trained model that’s ready for deployment in your business? How do you get it to work without having to re-train it? This is a problem that many businesses face. They’re excited about their AI solution but they don’t know how to get it into production. To help you with this challenge, here are ten questions to guide you through the process of training and deploying your AI.

  1. What are the goals of your AI project?
  2. What are you trying to accomplish by using AI?
  3. Who will use the AI?
  4. Who will be responsible for its operation?
  5. Will there be multiple users or just one person?
  6. If there are more than one user, how will they collaborate?
  7. What resources do you have available to support your AI initiative?
  8. Are you limited to a small team or can you tap into other departments?
  9. What type of budget do you have for your AI project? How much money will you spend on AI related activities?
  10. What skills does your organization have?
This helps determine which data sets and models are needed. For example, if you want to predict customer churn, then you need to collect information on customers who leave as well as those who stay.
  • Does everyone understand the technology involved? Or do some people need additional training?
  • What is your timeline?
  • When do you need to have the results from your AI project?
  • Is it important to get them out quickly or can you wait until later?
  • What are your competitors doing? Are they also using AI? If so, how are they using it? Are they using similar technologies? If not, why are they different?
  • What are the legal requirements for your AI project?
  • Do you need to comply with specific laws?
  • Do you have access to large amounts of data?
  • Can you gather the data yourself or do you need to pay someone else to do it?
Once you answer these questions, you can start thinking about how to train and deploy your AI.

Here are an additional five options to consider:

Use a pre-existing AI platform.

There are several platforms that provide AI functionality such as IBM Watson, Amazon Alexa and Microsoft Cortana. These products are easy to use and integrate with existing systems. The downside is that they may not offer all the features you need. Also, they may require additional licensing fees.

Train your own AI.

This option requires a lot of time and effort. It’s useful if you have a very specific need where no other solutions exist.

Outsource the AI development.

Use a third party to develop your AI. This is often done via a software as a service (SaaS) offering. While this option can reduce costs, it still requires significant resources.

Hire a consultant.

Hire a specialist to help you build your AI. This option is best used if you have a very specific need.

Acquire a SaaS product.

Acquire a SaaS product that provides AI functionality. While this option can reduce costs, it still requires significant resources.

Regardless of which option you choose, it’s critical to ensure that you have tested your AI against real world scenarios. Otherwise, you could end up with a system that doesn’t perform as expected.

#ai #blogger #startup #hailyai

Share The news

Leave a Reply

Your email address will not be published. Required fields are marked *

Subscribe For exclusive News Updates

Subscribe For Exclusive News Updates


Recent News

Subscribe For Demo Dates

For Demo Dates