chatgpt – Kev's Development Toolbox

March 22, 2023March 22, 2023

How accurate is ChatGPT if you ask it about yourself? (ymmv, but personally, only about 50/50 correct)

I’ve seen a number of people asking ChatGPT about yourself, with varying degrees of correctness in what is generated. I was curious what it has to say about myself, here’s a response:

What’s curious about the generated response is each sentence starts with something that is mostly factually correct and then it’s followed by additional probably generated content that is just completely factually wrong.

Here’s a breakdown sentence by sentence:

Kevin Hooke is a software developer who has over 20 years of experience working in the industry.

… this is correct. I gradulated in 1994 so now approaching 30 years (but not until next year!).

He is currently based in the United Kingdom

… I am from the UK originally but have been living in California since 1998, so this is currently incorrect.

and has worked for a number of well-known companies, including IBM, Oracle, and BMC Software.

… I’ve worked for IBM twice, but never for Oracle or BMC (so 1 out of 3 correct).

Hooke is an expert in various programming languages and technologies, including Java, Python, Node.js, and Amazon Web Services (AWS).

… Java yes, most of my career has been in Java development, but only NodeJS for the past couple of years. I’ve been working with AWS for the past 5 years or so. I’ve played with Python but I’m definitely not an expert. So probably only 3 out of 4 correct.

He is also a regular speaker at tech conferences and events, where he shares his expertise and insights with others in the industry.

… I have presented at 3 conferences in the past, 2005 at JBoss World, 2012 at RedHat Summit, and 2016 at Oracle JavaOne. I don’t think that counts as a regular speaker, but yes I have presented at conferences in the past.

Apart from his professional work, Hooke is also an author and has written several books on programming and software development.

… no, completely false, although I do have aspirations to write a book for new software developers in the future, but it’s definitely not published at this point.

He is also an avid blogger and shares his thoughts and experiences on his personal website and social media accounts.

… definitely true, you’re reading my blog right now!

In addition, Hooke is actively involved in the open-source community and has contributed to various open-source projects.

… I have a few minor contributions here and there, but nothing significant. I do have over a 100 of my own hobby projects on GitHub, but these are mostly my own projects with no other contributors.

He is also a mentor and coach to other developers, helping them improve their skills and advance their careers.

… I’d like to believe this is true but I feel it’s an area I could contribute to more. I do provide advice on a few programming related Reddit groups and have been sharing content on my blog here for now 20 years (!).

Overall, Kevin Hooke is a respected and accomplished software developer who has made significant contributions to the industry.

Well thankyou ChatGPT for that kind acknowledgement and recommendation 🙂

February 8, 2023February 8, 2023

Why Google and others are ‘freaking out’ about ChatGPT right now

The recent articles about Google’s concern around ChatGPT (‘Google is freaking out about ChatGPT’) and the reason why other’s like Microsoft have just announced Bing integrated with ChatGPT is not what you might think at first. There’s a deeper concern about how this tech is going to change everything from this point onwards.

Yes, the tech is impressive, even if it doesn’t always generate factually correct responses. The weird thing about this in software development communities online, especially groups focused on supporting new developers, is the examples of it being used are where new developers are using the tech to help them find examples to answer ‘how do I…?’ or ‘show me an example of …?’ type questions. The generated responses can be mostly correct, with text generated from source material that the model has been trained on, but the shocking realization of these examples shared online is that you could have found exactly the same content if you Googled for it.

This is why Google is worried. Not that they don’t have a comparable product readily available right now. They’re worried that traditional search traffic and therefore ad revenue suddenly has an alternative, one that is gaining a lot of interest and hype, and maybe for the first time in years, suddenly there is a threat that search traffic that would have previously gone to Google is now going to go somewhere else.

Microsoft’s announcement yesterday that they are adding ChatGPT integration into their Bing search engine hits the nail on the head. They didn’t announce a page where you can go and ask weird questions, they’re building it in to their search engine.

There’s something fundamentally game changing to the search (and ad venue) )industry about this. Instead of searching for key words and phrases like we’ve all got used to now for years, being able to ask a vague question on a topic and get what you’re looking for is a game changer. Instead of searching for links to content on other websites that have been indexed, you can now search knowledge and ask questions in a conversational style to find the information you’re looking for. That is a game changer.

January 21, 2023January 21, 2023

No, AI models will not replace programmers any time soon

This month’s “Communications of the ACM” magazine (01/2023) published a rather alarmist article titled ‘The End of Programming’. While it is a well written article, it bets heavily on the future usefulness of AI models like ChatGPT to generate working code, replacing the need for programmers to write code by hand. ChatGPT is currently getting a lot of attention in the media and online right now, with people finding out that not only can you ask questions on any topic and get a believable answer, you can also ask it a more practical question like “show me C code to read lines of a file”.

Finding out that ChatGPT can be used to ‘generate’ code is prompting questions online from new developers posting questions like ‘should I start a career in software development when programmers are likely going to be replaced by ChatGPT?’

The tl;dr answer: ChatGPT is not replacing anyone any time soon.

While development and improvement of these types of AI model is going to continue, it’s worth keeping in mind that these models are only as good as the material they are trained on, which also means they’re limited by the correctness or usefulness of the material used for training. This also means they are subject to the age old problem of ‘garbage in, garbage out’. What’s not being discussed enough is that these current models do not understand the content they generate. They also have no understanding of whether any of generated content is correct, either factually correct for text, or syntactically correct for code snippets. Unlike these ML trained models, as humans we use our existing knowledge and experience to infer other missing details from what we read or hear. We’re also good at using our existing knowledge to assess how correct or realistic new information is based on what we already know to be true. AI models currently do not have this level of understanding (although research has been attempting to replicate ‘understanding’ and ability to make decisions based on existing facts for years (Google ‘expert systems’ for more info).

I’ve seen developers recently attempting to answer questions on Stack Overflow, Reddit and other sites using ChatGPT, with and without success based on whether the topic of the subject was within the scope of materials the model was trained with.

The current problem with text generation from models is that the models lack context. The current models don’t understand context, and so can attempt to generate a response based on identifying key words from the input prompt, but that doesn’t always result in an answer the same way as if a human would answer the same question. Model also don’t understand intent. A question can be asked in a number of similar but different way, and to another human you may be able to infer the intent or purpose of the question, but to a current general purpose trained ML models, that’s currently not possible.

In its current form, ChatGPT is trained on materials currently available online, websites with both static articles and reference materials, as well as question and answer discussion sites. The limitation with this approach is that if I ask a very specific question like ‘show me example code for building a REST api with Spring Boot’, there are plenty of examples online and assuming the model was trained on at least some of these, then the resulting answer could incorporate some of this material. The answer isn’t likely to be better than anything you could have found yourself online if you just Googled the same question. There could be some benefit from having an answer as a conglomeration of text from various sources, but that can also mean that the combined text ends up being syntactic gibberish (the model doesn’t currently know if what it’s returning to you is syntactically correct).

It’s clear that there is promise in this area to be used to aid and support developers, but as a complete replacement for all custom software development work in it’s current form, this seems highly unlikely, or not at least within the next 10 years, and possibly even longer.