What are Large Language Models and How Can You Leverage It?

💡AI TRIVIA

Two years ago, OpenAI's Yuri Burda and Harri Edwards explored teaching language models basic math. They wanted to know how many addition examples it would take for the models to add any numbers. Initially, the models just memorized sums without solving new ones.

An accidental oversight left tests running for days instead of hours. When they checked back, they were surprised to find the models had learned to add after much longer training. Curious, they teamed up with others to see why this happened. Sometimes, models struggled, then suddenly got it, like a light switch. They called this "grokking."

“It’s fascinating,” says Hattie Zhou, an AI researcher not involved in the study. “Maybe models just need more time to learn.”

📕Quick Refresh

Large language models are foundation models trained with huge data sets. They can understand and create natural language and other content, handling many different tasks.

Large Language Models (LLMs) work with deep learning and loads of text. They run on transformers, great for text handling. Neural networks make them better by training on tons of data. The attention mechanism zeroes in on the important stuff.

In training, models predict the next word, assigning probabilities to each small token. Tokens, little bits of characters, turn into numerical embeddings that give context.

LLMs need billions of text pages to be accurate. They learn grammar, meanings, and links through zero-shot and self-supervised methods. Once ready, they create text by predicting the next word, making them perfect for understanding language and creating content.

📈 AI News

Here are some of AI News to watch out for and keep your eyes on:

Small Language Models?

Large language models (LLMs) need lots of computing power. Microsoft is working on small language models (SLMs) that are compact but capable. Introducing the Phi-3 family, they're top-notch and budget-friendly small models. Phi-3-mini, boasting 3.8 billion parameters, outperforms larger rivals. It's now available on Microsoft Azure, Hugging Face, Ollama, and as an NVIDIA NIM microservice.

Alibaba Enters the Fray

Alibaba's upping its AI game with the Qwen2-Math models, beating OpenAI’s GPT-4o in math. Over the past year, the Qwen team in Alibaba's cloud division has focused on enhancing these models' math reasoning skills. They come in three sizes based on parameter count, which affects how AI learns and responds. The largest, Qwen2-Math-72B-Instruct, outperformed US models in math tests, including those by GPT-4o, Anthropic, Google, and Meta. Tested on English and Chinese benchmarks like GSM8K and OlympiadBench, these models aim to tackle complex math challenges, including China’s tough gaokao exam.

AI Index

The AI Index is an annual report by AI experts from business and academia. It tracks AI trends, covering research, tech, ethics, economy, policies, and public views. Built on solid data, it helps policymakers and business leaders understand AI developments.

Investments

Business leaders are paying attention. Global private investment in generative AI shot up from $3 billion in 2022 to $25 billion in 2023. Nearly 80% of Fortune 500 earnings calls mentioned AI. Data shows AI boosts worker productivity, especially for those with lower skills.

Policies

In 2023, lawmakers globally mentioned AI 2,175 times, nearly doubling the previous year. The US introduced 25 AI-related laws, tackling copyright for AI content and cybersecurity risks. It was a big year for AI policies: the EU launched its comprehensive AI Act, and President Biden unveiled an Executive Order on AI.

Public View

AI's got folks a bit jittery! Back in 2022, 38% of Americans were more worried than excited about AI. By 2023, that shot up to 52%. Worldwide, 52% felt uneasy, marking a 13% rise from the year before.

Read the full AI Index report here.

🛠️ Leveraging AI in Your Business

 Here are some ways on how you can leverage AI better in your business through definitive tips in LLMs:

Faster Content

Imagine having a writing assistant that never sleeps and always delivers top-notch content at lightning speed. That's what LLMs bring to the table. These language models craft articles that are not just quick but also hit the mark in quality. They understand context, style, and even the subtle nuances that make content engaging. Need an article turned around fast for a tight deadline? LLMs have your back.

Less effort and time

LLMs like ChatGPT, Gemini, CoPilot slice through the time you used to spend brainstorming, editing drafts, and polishing paragraphs. It’s like having a trusty sidekick that never tires, always ready to help you whip up articles, reports, or blog posts. You get to focus more on your creative vision while the LLM handles the nitty-gritty, making content creation feel like a breeze.

LLMs Remember

It’s called a language model for a reason. They remember previous prompts, data, and what you are looking for. These are stored in the different conversations you hold with an LLM. Think of a language model as a chatty friend who remembers past talks. It's like having a notebook that keeps track of your questions, ready to pull out the right info when needed. Each chat builds on the last, making your experience and result more personalized.

🔧 Secrets of the Trade

Here are some best secrets of the trade by the masters themselves. Try them out, and experiment a little bit:

Have SOPs

Standardize your process by having a standard operating procedure. Make a list of themes or things that you usually ask from an LLM. For example, you are a content writer, and usually ask ChatGPT to make blogs, then have a dedicated list for what you want to expect from ChatGPT. The same goes for other things you’d want to ask as well. Rinse-repeat the process, experiment a little bit for best results, then you have a list of prompts to use saving you more time and energy.

Personalized Prompts

There are good prompts, and there are great prompts. The difference between the two are the great prompts are comprehensive, tailored, and asks for specific results. Here are examples of great prompts to use:

1.) ”Act like X”

-You can ask any LLM to act like something. For example, “I need you to write me a blog about “different cat breeds and which breed is best for a beginner”. Act like an expert veterinarian and give me results” This usually gives a more tailored and better response as you have given the LLM an idea of what you are expecting, and how it should act.

2.) ”Ask questions”

-This is the super prompt to ensure quality content. Whenever you want an LLM to do something, make sure to add, “Ask Questions to help you understand what you need to do”. This way, the LLM will provide you with a list of questions you have to answer first before proceeding to the result that it’s going to put out.

3.) “Think before you write”

-Integrate this prompt whenever you are making or attempting to make more quality content. With LLMs, it usually predicts the next word or sentence from the given phrase or prompt. But using this prompt, the LLM reads the previously written words and patterns to generate new content from, this means that you have a better chance of matching “bread and butter” rather than “bread and shoelaces”.

🚀 Quick Wins

Document everything

The process of documentation works wonders. If you have proper documentation of the different results per prompt, what you adjusted, you’ll never feel lost and will always have a perfect prompt for everything.

Have content ready but be prepared to personalize

LLMs generate content fast but don’t expect it to be perfect every time. Especially with Google’s new updates it might mark you as spam. Tailor your content to your target audience, make sure it provides value. The best way to use LLMs is to get over creativity block and not necessarily be fully-dependent on that content.

Tailored Conversations

You can tailor LLMs to have multiple personalities. The different conversations you have with an LLM is stored, remembered, and brought back whenever you use it. It is recommended to have one particular theme or topic for every conversation with an LLM. For example, you might be content writer and trying to write about “Cryptocurrency”, that should stand as one theme therefore one conversation. Any other topics should go on a different conversation to have more tailored results.

🔥 Hot Takes

We, as humans have reached the point that everything should be fast and efficient, and in some cases, we forget that we need to bring value.

Don’t make it about you, make it about the value.

🤔 Intrigued by AI's Potential, But Unsure of the Next Step?

We get it! This issue might have you brimming with possibilities, but where do you begin? The AI StandUp is made with ❤️ by The BrainTrust and we are here to bridge the gap. Head over to our website, or simply reply to this email with your specific questions. Let's turn your AI curiosity into a game-changing reality.

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