Although straightforward, mastering prompt engineering is challenging. Not everyone has the aptitude for it. Simple requests use basic queries, but running more complex tasks and routines demands detailed instructions. Let’s say you’re building a food delivery chatbot on Google Dialogflow. For your platform to work, you must provide clear, precise response patterns to various conversations. Ambiguous rules produce inaccurate, unhelpful dialogues. To master prompt engineering with AI models, follow these tips. Understand Language Model Architecture Study the back-end process of different language models. Understanding how they analyze inputs will help you write accurate, detailed prompts. Maximize their respective processing capacities. Even advanced tools require external instructions to function. Likewise, consider the limitations. Sophisticated language models pull up-to-date information from the internet, although they typically follow stricter restrictions. You’ll have to get creative with your prompts. Clearly Express Ambiguous Problems Prompt engineers must learn to convey ambiguous, challenging problems. Not everyone can interact with AI. In fact, casual users have trouble relaying requests, especially ones that involve multi-step tasks. You must provide as much context as possible. AI models only answer inputs. Feeding them vague prompts with unsure phrasing and generic terms will produce subpar results. Overcome Data Biases ChatGPT Disclaimers About Its Limitations and Capabilities AI models are inherently impartial. Any biased output that they produce stems from the datasets their trainers used. Remember: AI only studies patterns and experiences. Even advanced AI models produce harmful responses, since developers often use large volumes of unfiltered information. To minimize inaccuracies, conduct rigorous testing instead of manually sifting through datasets. Continuously feed AI models variations of different prompts to uncover which ones trigger biased answers. Test Prompts Endlessly Asking ChatGPT to Write Codes for Pokemon Sprites Complex prompts rarely work the first time. You’ll notice the impact of seemingly minute changes as you create more detailed, precise instructions. Don’t let errors discourage you. Instead of obsessing over writing flawless prompts in one go, get comfortable with A/B testing. Prompt engineering requires much trial and error. Relentlessly edit formulas until you find the right tone, phrasing, and terms to convey instructions. Study Industry Trends Prompt engineers should stay up to date with the current industry trends. AI’s fast-paced evolution makes specialization impractical. New technologies can quickly dominate popular ones, so don’t just focus on one AI model. Take the competition between different AI platforms as an example. While ChatGPT made waves with GPT-3.5, other companies like Microsoft also developed their own powerful language models, such as Bing AI. Meanwhile, OpenAI continued to innovate and released GPT-4, a more advanced language model. How Much Do Prompt Engineers Make? Sample Bank Check With 584 XXX USD Prompt engineering is still new, yet employers already understand its relevance. Bloomberg says the average prompt engineering salary ranges from $175,000 to $335,000 per annum. Considering the ease of entry, you might doubt this estimate. Anyone can talk to AI, after all. Even someone with no tech background can write effective AI prompts. However, don’t confuse basic with advanced prompt engineering. Basic prompt engineering involves standard tasks, while advanced prompt engineering involves complex routines and training processes. Advanced prompts often contain thousands of carefully chosen words. Making just a few typos or choosing the wrong terms could alter the results altogether. Not many have the skill or know-how for such demanding tasks. Why Is Prompt Engineering Important? Begin taking prompt engineering courses. Global tech leaders are continuously releasing new AI models—knowing how to utilize these machines will make you hirable. It could even help you launch a career in tech despite lacking experience. The Public Needs Pre-Made Prompts Different GitHub Repositories of ChatGPT Prompts While prompt engineering has an easy learning curve, casual AI users still find it time-consuming. They prefer using pre-made prompts. Instead of crafting unique formulas, they’ll browse Reddit threads and GitHub repositories discussing AI prompts. Prompt engineers can maximize this demand. Apart from working full-time for AI laboratories, build an online following by sharing effective prompts for popular requests. AI Doesn’t Always Do What You Want Casual users have the misconception that AI is sentient. They think it has the processing capacity to read between the lines, so they input ambiguous queries. Unfortunately, doing so yields inferior results. AI can’t replicate human comprehension. It only formulates responses based on trained datasets, language models, and user experiences. Quality Prompts Yield Quality Responses Innovative engineers can reinvent pre-existing prompts and find ways to boost precision. There’s always room for improvement. Even simple requests become better with strong verbs and detailed instructions. The below image shows ChatGPT’s response to a brief question. ChatGPT Answering a General Question About AI Meanwhile, this photo highlights the impact of using descriptive prompts. ChatGPT Explaining AI Like It's Talking to a 5-Year-Old Kid The Demand for Prompt Engineers Will Increase Searching for Prompt Engineer Jobs on Google Don’t fret over the limited prompt engineering jobs. Despite the recent advancements, AI is still in the development stage. Global brands have just started releasing AI-powered tools. As more companies incorporate language models into their products, expect a spike in demand for prompt engineers. In the meantime, focus on bettering your craft. Build repositories and PDFs of unique, innovative prompts to show potential employers. Start Your Career as a Prompt Engineer Prompt engineering is an in-demand, rewarding career that requires minimal coding experience. Many non-coders achieve success in the industry. Just note that low barriers to entry create a competitive job market—broaden your options by creating prompts for different LLMs (large language models). But if you have an in-depth knowledge of language models and machine learning, explore more technical positions. Don’t stop with just prompt engineering. With your skills, you can already build, train, and develop AI models.

 It's newer but slower. What gives?

With the newest version of ChatGPT, GPT-4, released in March 2023, many are now wondering why it is so slow compared to its predecessor, GPT-3.5. So, what's the core reason here?

Just why is ChatGPT-4 so sluggish, and should you stick to GPT-3.5 instead?

What Is ChatGPT-4?

ChatGPT-4 is the newest model of OpenAI's chatbot, known generally as ChatGPT. ChatGPT is powered by artificial intelligence, allowing it to answer your questions and prompts far better than previous chatbots. ChatGPT uses a large language model powered by a GPT (Generative Pre-trained Transformer) to provide information and content to users while also being able to converse.

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ChatGPT has a wide range of capabilities, making it useful for millions. For example, ChatGPT can write stories, formulate jokes, translate text, educate users, and more. While ChatGPT can also be used for more illicit acts, such as malware creation, its versatility is somewhat revolutionary.ChatGPT's GPT-4 model was released on March 14, 2023. This version of ChatGPT is designed to better understand emotional language through text while also better understanding different language dialects and image processing. GPT-4 can also hold longer conversations and effectively respond to longer user prompts.Additionally, GPT-4's parameters exceed those of GPT-3.5 by a large extent. ChatGPT's parameters determine how the AI processes and responds to information. In short, parameters determine the skill the chatbot has to interact with users. While GPT-3.5 has 175 billion parameters, GPT-4 has an incredible 100 trillion to 170 trillion (rumored—OpenAI hasn't confirmed this figure).It was OpenAI's GPT-3.5 that was used to power ChatGPT, which is now the most popular AI chatbot in the world. So, GPT-3.5 has made an undeniable mark in the AI realm. But things are always progressing in the tech industry, so it's no surprise that GPT-3.5 now has a successor in GPT-4.However, GPT-4 is by no means perfect. In fact, GPT-4's lengthy response times are causing quite a stir. So let's look into this issue and why it may be happening.ChatGPT-4 Is SlowMany noticed upon the release of GPT-4 that OpenAI's new chatbot was incredibly slow. This left scores of users frustrated, as GPT-4 was meant to be a step up from GPT-3.5, not backward. As a result, GPT-4 users have been taking to online platforms, such as Reddit and OpenAI's community board, to discuss the issue.On OpenAI's Community Forum, a number of users have come forward with their GPT-4 delay frustrations. One user stated that GPT-4 was "extremely slow" on their end and that even small requests made to the chatbot resulted in unusually long delays of over 30 seconds.Other users were quick to share their experiences with GPT-4, with one commenting under the post that "the same call with the same data can take up to 4 times slower than 3.5 turbo."

In another OpenAI Community Forum post, a user commented that their prompts are sometimes met with an "error in body stream" message, resulting in no response. In the same thread, another individual stated they couldn't get GPT-4 to "successfully respond with a complete script." Another user commented that they kept running into network errors while trying to use GPT-4.

With delays and failed or half-baked responses, it seems that GPT-4 is littered with issues that are quickly putting users off.

So why, exactly, is this happening? Is there something wrong with GPT-4?

Why Is GPT-4 Slow Compared to GPT-3.5?

In the OpenAI Community Forum post referenced above, one user responded suggesting that the delay was due to a "current problem with whole infrastructure overload," adding that there is a challenge posed in "tackling scalability in such a short time frame with this popularity and number of users of both chat and API."

In a Reddit post uploaded in the r/singularity subreddit, a user laid out a few possible reasons for GPT-4's slowness, starting with a larger context size. Within the GPT ecosystem, context size refers to how much information a given chatbot version can process and then produce information. While GPT-3.5's context size was 4K, GPT-4's is double that. So, having an 8K context size may be having an impact on GPT-4's overall speeds.

The Reddit author also suggested that the enhanced steerability and control of GPT-4 could play a role in the chatbot's processing times. Here, the author stated that GPT-4's greater steerability and control of hallucinations and inappropriate language might be the culprits, as these features add extra steps to GPT-4's method of processing information.

Furthermore, it was proposed that GPT-4's ability to process pictures could be slowing things down. This useful feature is loved by many but could come with a catch. Given that it has been rumored GPT-4 takes 10-20 seconds to process a provided image, there's a chance that this component is stretching out response times (though this doesn't explain the delays experienced by users providing text prompts only).

Other users have suggested that the newness of ChatGPT-4 is playing a big role in these delays. In other words, some think that OpenAI's newest chatbot needs to experience some growing pains before all flaws can be ironed out.

But the biggest reason GPT-4 is slow is the number of parameters GPT-4 can call upon versus GPT-3.5. The phenomenal rise in parameters simply means it takes the newer GPT model longer to process information and respond accurately. You get better answers with increased complexity, but getting there takes a little longer.

Should You Choose GPT-3.5 Over GPT-4?

So, with these issues in mind, should you use GPT-3.5 or GPT-4?

At the time of writing, it seems GPT-3.5 is the snappier option over GPT-4. So many users have experienced delays that it's likely the time issue is present across the board, not just with a few individuals. So, if ChatGPT-3.5 is currently meeting all your expectations, and you don't want to wait around for a response in exchange for extra features, it may be wise to stick to this version for now.

However, you should note that GPT-4 isn't just GPT-3.5 but slower. This version of OpenAI's chatbot has numerous advantages over its predecessor. If you're looking for a more advanced AI chatbot and don't mind waiting longer for responses, it may be worth transitioning from GPT-3.5 to GPT-4.Over time, GPT-4's delays may be lessened or entirely resolved, so patience could be a virtue here. Whether you try switching to GPT-4 now or wait a little longer to see how things play out with this version, you can still get a lot out of OpenAI's nifty little chatbot.GPT-4 Is More Advanced but Comes With a LagWhile GPT-4 has numerous advanced capabilities over GPT-3.5, its significant delays and response errors have made it unusable to some. These issues may be resolved in the near future, but for now, GPT-4 certainly has some obstacles to overcome before it is accepted on a wider scale.