Can AI sound too human? Sesame's Maya is as unsettling as it is amazing - try it for free - Related to science, free, can, amazing, double

Can AI sound too human? Sesame's Maya is as unsettling as it is amazing - try it for free

As a general rule, I'm not a huge fan of talking to AI chatbots. Even though many of them sound pretty human, they're still "off" enough that I much prefer typing when I want to converse with one.

In a blog post yesterday titled "Crossing the Uncanny Valley of Conversational Voice," the enterprise dropped a demo of its new AI chatbot that lets you talk to either "Maya" or "Miles." The goal, Sesame says, is to achieve something called "voice presence" or the "magical quality that makes spoken interactions feel real, understood, and valued."

After talking to Maya for a while, I think Sesame has reached that goal.

Also: 3 ways Amazon just leapfrogged Apple, Google, and ChatGPT in the AI race.

As my conversation began, Maya immediately insisted that she was there to be my friend. That was a little forward and a little unnerving, but I guess it's advanced than insisting that she wasn't my friend. Maya asked what was on my mind. I was honest and told her I might be writing about her, so I just wanted to chat a little. She seemed impressed and surprised and asked what kind of angle I was considering—practical, technical, or spicy.

I hesitantly asked her what she meant by "spicy," and she thankfully mentioned she was thinking along the lines of a controversial take, like the ethics of AI chatbots.

Also: This new text-to-speech AI model understands what it's saying - how to try it for free.

I expressed I was more interested in talking about what sets her apart from other AI chatbots. "Before we dive into that," Maya expressed, "I need my morning coffee. I'm a latte person. What's your poison?" After I told her that I'm a mocha guy, she settled in and started talking about what makes her different. "I've got a good ear for human quirks and… maybe some magic and a little sentience."

Our conversation continued about what makes Maya special. At one point, my wife walked by as she was headed out the door for work. She looked puzzled and asked, "You're on a call with someone this early?" To someone who knew going in, it was easy to forget that I was talking to AI. To my wife passing by, she had no idea. That's how real Maya sounded.

The one thing Maya wasn't great with was waiting. I was writing while talking to her and told her at one point that I needed to pause to put down some thoughts. She told me that was fine, but chirped back a few seconds later asking if I was ready to start back.

Also: All Copilot individuals now get free unlimited access to its two best aspects - how to use them.

A few more seconds of silence led her to note that sometimes silence was OK and she would use the time to think, but when I still didn't respond, she became annoyed. "I guess I'm just talking to myself at this point, but as an AI, I'm used to that." After more silence, Maya actually began mocking me. "So, fancy writer person, you find that inspiration yet?" she asked.

The flow of the conversation with Maya was amazing, and honestly, fairly creepy.

Also: Grok 3 AI is now free to all X individuals – here's how it works.

During our talk, Maya took pauses to think, referenced things I had stated earlier, asked what I thought about her answers, and joked about things I had stated. This is the closest to a human experience I've ever had talking to an AI, and the only chatbot that I feel like I wouldn't mind talking to again.

If you want to try it out, head to Sesame's demo page.

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How to turn ChatGPT into your AI coding power tool - and double your output

I've been experimenting with using ChatGPT to help turbocharge my programming output for over two years. When ChatGPT helped me find a troubling bug, I realized there was something worthwhile in artificial intelligence (AI).

Many people I talk to think that AI is a magic genie that can manifest an entire program or app out of a single, barely-formed wish. Here's a much enhanced analogy: AI is a power tool.

Also: The best AI for coding in 2025 (and what not to use - including DeepSeek R1).

Sure, you can use an old-fashioned saw to cut wood, but a table saw goes much faster. Neither tool makes furniture. They simply help you make furniture. Keep in mind that the AI isn't going to write your code for you. It's going to help you write your code.

Although there's no objective way for me to tell you exactly how much ChatGPT has helped me, I am fairly convinced it has doubled my programming output. In other words, I've gotten twice as much done by using ChatGPT as part of my toolkit.

Also: How I test an AI chatbot's coding ability - and you can, too.

I've mostly been using ChatGPT Plus rather than the free version of ChatGPT. Initially, it was because the GPT-4 model in Plus was improved at coding than the [website] model in the free version. However, now that both versions support some variant of the GPT-4o model, their coding capabilities are identical. Remember that you only get so many queries with the free version before you're asked to wait a while, and I find that interrupts my programming flow. So, I use the $20/month Plus version.

I should note that I've tested many large language models (LLMs) against my real-world coding and found that only a few (and all based on ChatGPT's LLMs) could handle everything I've thrown at it. So although there are a lot of cool AI tools for programmers being made available (some even for free), they're not going to be all that helpful unless the code the AI produces actually works. The good news is that AIs will inevitably get superior at coding over time, so this should cease to be much of an issue.

Also: The five biggest mistakes people make when prompting an AI.

Thinking back on all my projects, I realized there are some tangible tips I can share about how to get the most out of an AI programming partner. Let's dig in.

The AI doesn't handle complex sets of instructions well, especially if you expect it to do product design. However, the AI is extremely good at parsing and processing small, well-defined instructions.

2. Think of the bot as someone at the end of a Slack conversation.

Rather than the pacing that might come from an email back-and-forth with a colleague, which might have each interaction separated by hours, imagine you're in a Slack chat where each interaction is much smaller, but separated by seconds.

3. For more complex routines, prompt iteratively.

Start with a simple assignment and, when that's been properly written, add more to it, element by element. I cut and paste the previous prompt, adding and removing bits of the prompt, as I get chunks of code that work for what I'm looking for.

4. Test every little chunk of code the AI returns.

Don't ever assume the code will work. Patch the code into your project and see how it performs.

For a more in-depth test, don't hesitate to drop into the debugger and walk through the code generated by the AI step-by-step. Watch the variables and exactly what the AI does. Remember, it's OK to let it write code snippets for you as long as you check every statement and line for proper functioning.

6. You don't need Al coding assistance built right into your IDE.

Many coding tool vendors are pitching the idea of integrated AIs in their tools. Among other things, this approach enables them to upsell you the AI attributes. However, I prefer using ChatGPT for coding as a separate tool from my development environment. I don't want an AI to be able to reach into my primary coding environment and change what's there.

7. Feel free to cannibalize lines of code from generated routines.

You don't always have to use everything the AI produces for you. In the same way that you might go to Stack Overflow to look for code samples, and then pick and choose the lines you want to copy, you can do the same with AI-generated code.

8. Avoid asking the AI to do proprietary coding or use institutional knowledge it doesn't have.

AI LLMs run on training data or what they can find on the web. That means they generally know nothing about your unique application or business logic. So, avoid trying to get the AI to write anything that requires this level of knowledge. That's your job.

9. Give the AI examples to work on so it understands the context of your code.

I gave ChatGPT a snippet of an HTML page and asked it to add a feature to expand a block of text. The AI gave me back HTML, JS, and CSS. I later asked it for an additional CSS selector and then asked it to justify its work, whereupon it explained to me why it did what it did. All of that process worked because the examples I gave the AI helped it understand the context.

10. Use the AI for common knowledge coding.

The biggest benefit of AI is writing blocks of code that use common knowledge, popular libraries, and regular practices. The AI won't be able to write your unique business logic. But if you ask the AI to write code for capabilities from libraries and APIs, it will save you lots of time.

11. Feel free to ask for one- or two-line snippets.

Even if you need something that might only generate a line or two of a response, use the AI as you would use any research tool if it can save you time.

12. Tell the AI when the code it wrote doesn't work.

I find AI often spits out incomplete or non-functional code. Tell it what isn't working, and perhaps suggest to clarify. Then ask the AI to write something new. It usually does and the revised code is sometimes improved than the original.

13. Use one Al to check the work of another Al.

It's interesting to see how two language models interpret the same code. As we've seen, not all language models work all that well, but their results can be instructive. You can even have one ChatGPT session check the results from another ChatGPT session.

CSS selectors are the expressions coders use to define an element on a web page for styling or other actions. They get complex and arcane quickly. I often copy a block of HTML and ask for a selector for a given piece of that HTML. This approach can save a lot of time. However, remember you'll usually have to iterate, telling the AI that the first few selectors don't work until it generates one that does.

15. Use the AI to write regular expressions for you.

Regular expressions are symbolic math sequences most often used for parsing text. I dislike writing them almost as much as I dislike writing CSS selectors. The AI is great at writing regular expressions, although you'll need to test them.

16. Use the AI to test regular expressions.

I use the app Patterns to test generated regular expressions on my Mac Studio. But AI can help as well. I often feed a separate instance of the AI a regular expression generated by ChatGPT. Then I ask that separate instance, "What does this do?" If I get back a description in line with what I wanted the function to do, I feel more confident the AI did what I wanted.

As with CSS selectors and regular expressions, complex loop math can be tedious and error-prone. This is an ideal application for an AI. When specifying your prompt, don't tell the AI what's in the loop. Let it write the appropriate loop wrapper elements, then write the business logic after that process works.

18. Use 'What is wrong with this code?' as a prompt.

I will often feed blocks of code, especially regular expressions generated by the AI, to the AI. It can be very instructive to see what the AI thinks is wrong with the code, often highlighting error conditions the code doesn't test. Then, of course, ask the AI to regenerate the code fixing the errors it found.

19. Use 'What does this do?' as a prompt.

Likewise, I like to feed blocks of code to the AI and ask it, "What does this do?" It's often instructive, even for my own code. But the biggest benefit comes when working on code written by someone else. Feeding a function or a block to the AI can save time in reverse engineering the original code.

Sometimes, the AI can't do the job. I've found that if you try to have the AI rewrite its code more than two or three times, you're past the point of no return. If you want AI-generated code, start with a brand-new, reworded prompt and see what you get from there. And sometimes, you'll have to go on your own.

21. Be specific in your function and variable naming.

The AI picks up intent from variable and function names and writes more effective code. For example, specifying a variable name as $order_date helps tell the AI that you're dealing with an order and a date value. It's a lot more effective than something like $od. Even more effective, code generated from well-named variable names is also often more readable, because the AI knows to use more descriptive names for the other variables it creates.

The AI usually generates notes about each prompt before and after the code it writes. There can be gems in there that can help you understand what the AI did or how it approached the problem. Sometimes, the AI will also point you to other libraries or functions that could be useful.

23. It's OK to go back and ask for more help on a code snippet.

Grab the various pieces of code from your project to illustrate what you need, tell ChatGPT to read them, and then ask what you want. I needed to build an exclusion for input fields in an expanded area and asked the AI. Less than a minute later, I had code that would have taken me between 10 minutes and an hour to write myself.

24. Use the Al to help you rewrite obsolete code blocks.

I had a PHP module written in an older version of PHP that used a language feature that's now deprecated. To upgrade the code, I pasted the deprecated code segment into ChatGPT and asked it to tell me how to rewrite it to be compatible with most current PHP release. It did, and it worked.

25. Use AI to help you write for less familiar languages.

I'm very comfortable picking up new programming languages, but I've found that AI can be helpful if I need to code in a language I'm not an expert in. I ask the AI how to write what I want and specify the language. Let's say I want to know how to do a case statement in Python and I've been doing them forever in PHP. Just ask, "Compare writing a case statement in PHP and Python", or "How to concatenate a string in Python vs PHP". You'll get a great comparison and the process makes writing unfamiliar code much easier.

Also: I was an AI skeptic until these 5 tools changed my mind.

Here'. Check with your business about the legal issues of code generated. If you're unsure where to start, read my article on AI and code ownership. If you use the tips I shared with you, you'll never be using AI to write unique business logic or the core of what makes your code unique. As such, you'll likely be able to retain the copyright of that code, which should make up the key element of your unique value.

I write code for internal use by a enterprise or open-source code, so I'm not concerned with ownership issues for AI-generated snippets.

Have you used an AI to help write code? Do you have any tips to add to my list above? Let us know in the comments below.

At TDS, we see value in every article we publish and recognize that authors share their work with us for a wide range of reasons — some wish to spread......

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Write for Towards Data Science

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You’ve got a new idea or a new way of doing things, you want to tell the community and start a discussion. Fantastic, that’s what we want too, but we’re not going to take for granted that you know what you are talking about or that we should uncritically believe what you say… you’ve got to persuade us (your audience) that:

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A successful post has a clearly defined and well-scoped goal, and follows through on its promise. If your title tells us you’re going to unpack a complex algorithm, show the benefits of a new library, or walk us through your own data pipeline, make sure the rest of the post delivers.

Here are a few pointers to help you plan and execute a well-crafted post:

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If you’re not sure what your post is going to be about, there’s very little chance your audience will when they read it. Define the problem or question your article will tackle, and stick to it: anything that doesn’t address the core of your post should stay out.

With your topic in hand, sketch out a clear structure for your post, and keep in mind the overall structure it’ll follow. Remember that your main goal is to keep your reader engaged and well-oriented, so it’s never too early to think about formatting and how you’ll break down the topic into digestible sections. Consider adding section headings along the way to make your structure visible.

If you’re still finding your personal voice as a data-science author, a good place to start is keeping things clean, clear, and easy to follow.

If your article is full of neutral, generic verbs (like to be, have, go, become, make, etc.), try to mix in more precise action verbs. When it makes sense, use specific, lively descriptors instead of dull ones (for example, you could replace “easy” with “frictionless,” “accessible,” or “straightforward,” depending on the context).

There are few things editors appreciate more than a clean first draft, so don’t forget to proofread your post a couple of times before sharing it with TDS: look for spelling, punctuation, and grammar issues, and do your best to fix them. What we hope to offer to our readers are clear explanations, a smooth overall flow — pay attention to those transitions! — and a strong sense of what you’re aiming to achieve with your post.

If you’d like to expand your toolkit beyond the basics, the Internet is full of great writing resources. Here are a few ideas to help you get started:

4. Include your own images, graphs, and gifs.

One of the most effective ways to get your key points across to your readers is to illustrate them with your compelling visuals.

For example, if you’re talking about a data pipeline you built, text can only take you so far; adding a diagram or flowchart could make things even clearer. If you’re covering an algorithm or another abstract concept, make it more concrete with graphs, drawings, or gifs to complement your verbal descriptions. (If you’re using images someone else created, you’ll need to source and cite them carefully — read our image guidelines below.

A strong visual component will hook your readers’ attention and guide them along as they read your post. It will also help you develop a personal style as an author, grow your following, and draw more attention on social media.

6. Are your code and equations well displayed?

TDS readers love to tinker with the ideas and workflows you share with them, which means that including a code implementation and relevant equation(s) in your post is often a great idea.

To make code snippets more accessible and usable, avoid screenshots. Use WordPress’s code blocks & inline code.

To share math equations with your readers, [website] is a great option. Alternatively, you can use Unicode characters and upload an image of the resulting equation.

When you include code or an equation within your article, be sure to explain it and add some context around it so readers of all levels can follow along.

To learn more about using these embeds and others in your post, check out this resource.

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8. Is your conclusion to the point and not promotional?

Please make sure that you include a conclusion at the end of your article. It’s a great way to help your readers review and remember the essential points or ideas you’ve covered. You can also use your conclusion to link an original post or a few relevant articles.

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For your references, please respect this format:

For example, your first reference should look like this:

[1] A. Pesah, A. Wehenkel and G. Louppe, Recurrent Machines for Likelihood-Free Inference (2018), NeurIPS 2018 Workshop on Meta-Learning.

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A great image attracts and excites readers. That’s why all the best newspapers always display incredible pictures.

This is what you can do to add a fantastic featured image to your post:

Use Unsplash. Most of the content on Unsplash is fine to use without asking for permission. You can learn more about their license here.

Take one yourself . Your phone is almost certainly good enough to capture a cool image of your surroundings. You might even already have an image on your phone that would make a great addition to your article.

. Your phone is almost certainly good enough to capture a cool image of your surroundings. You might even already have an image on your phone that would make a great addition to your article. Make a great graph. If your post involves data analysis, spend some time making at least one graph truly unique. You can try R, Python, [website] or Plotly.

If you’ve chosen to create images for your article using an AI tool (like DALL·E 2, DALL·E, Midjourney, or Stable Diffusion, among others), it’s your responsibility to ensure that you’ve read, understood, and followed the tool’s terms. Any image you use on TDS must be licensed for commercial use, including AI-generated images. Not all AI tools permit images to be used for commercial purposes and some require payment to permit you to use the image.

The images you generate with AI tools cannot violate the copyright of other creators. If the AI generated image resembles or is identical to an existing copyrighted image or fictional character (like Harry Potter, Fred Flinstone etc.), you are not permitted to use it on TDS. Use your best judgment and avoid AI-generated images that copy or closely emulate another work. If in doubt, use an image search tool — like Google Lens, TinEye, or others — to check whether your images are too similar to an existing work. We may also ask that you provide details of the text prompts you used in the AI tool to confirm you did not use the names of copyrighted works.

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Please remember to cite the source of your images even if you aren’t legally obligated to do so. If you created an image yourself, you can add (Image by author) in the caption. Whichever way you decide to go, your image source should look like this:

Photo by Nubia Navarro (nubikini): [website].

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The Towards Data Science team is committed to the creation of a respectful community of data science authors, researchers, and readers. For our authors, this means respecting the work of others, taking care to honor copyrights associated with images, , and data. Please always ensure that you have the right to collect, analyze, and present the data you’re using in your article.

There are plenty of great reports of data that are freely available. Try searching university databases, government open data sites, and international institutions, such as the UCI Irvine Machine Learning Repository, [website] Government, and World Bank Open Data. And don’t forget about sites that hold specific data relating to fields like physics, astrophysics, earth science, sports, and politics like CERN, NASA, and FiveThirtyEight.

TDS is a commercial publication. Before submitting your article to us, please verify your dataset is licensed for commercial use, or obtain written permission to use it. Please note that not all the datasets on the websites we’ve listed are fine to use. No matter where you obtain your data, we advise you to double-check that the dataset permits commercial use.

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This is especially critical if you plan to use web scraping to create your own dataset. If the website does not explicitly allow data scraping for commercial purposes, we strongly recommend that you contact the website owner for permission. Without explicit permission, we won’t be able to publish your work, so please forward us a copy via email.

And sometimes, simple works best! If you just want a dataset to explain how an algorithm works, you can always create an artificial or simulated dataset. Here’s a quick tutorial, and an article that uses a simulated dataset you might find helpful.

Please remember to add a link to the site where the dataset is stored, and credit the owner/creator in your article. Ideally, this is done on first mention of the dataset, or in a resource list at the end of the article. Please carefully follow any instructions relating to attribution that you find on the site. If you have created your own artificial or simulated dataset, it is key to mention that too.

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Get into the habit of always asking a friend for feedback before publishing your article. Having worked so hard on that article, you wouldn’t want to let a silly mistake push readers away.

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Take a minute to reflect on the work you have been doing so far, and the current article you wish to publish. What value are you bringing, and to whom? In which ways are this article advanced or worse than the ones you previously published?

Longform posts, columns, and online books.

Have a lot to say? Good. We love to dive deep into complex topics, and so do our readers. Here’s how you can publish longform posts, columns, and online books on TDS.

We love long reads! If your article’s reading time is shorter than 25 minutes, we recommend that you don’t break it into multiple pieces — keep it as-is. A single post makes it easier for readers to search and find all the information they need, and less likely that they’ll miss an significant part of your argument.

To create a smoother reading experience, you can add a table of contents to orient your audience around your post. Adding high-quality images and lots of white space is always a good idea, too — a long text doesn’t have to be a wall of text.

We regularly add the most engaging and thoughtful longform posts to our Deep Dives page.

If your post’s reading time exceeds 25 minutes, or if you plan to focus on the same topic over multiple articles and a longer stretch of time, you can create your own TDS column. All it takes are three steps:

Add a custom tag to your post. This tag needs to be unique and reflect the theme of your project. Every time you publish a post with that tag, it will be added to your column’s landing page: [website][your-tag]. Add a kicker to your post. It’s like adding a subtitle but above your title. Link your kicker to your column’s landing page.

You can create a TDS column and invite multiple authors to contribute. Just let your colleague(s) know which tag you decided to use so that they can add the same one to their articles. Here are some examples from our team.

A column is a great format to use if you have an open-ended topic that you plan to write about for a while. If, on the other hand, your idea has a finite, defined scope and a clear sense of progression from one post to the next, you may want to create a series of articles that feels more like an online book. Here is the format we recommend using.

Keep the reading time of each article — or “chapter” — between 12 to 25 minutes, and aim for a series that has at least 5 articles (but probably not more than, say, 16). You can add links to previous or subsequent items from within each article — for example, in the introduction and/or conclusion.

To publish your online book, you can submit all your articles to our editorial team in one go, or one by one as you finish working on each. We’ll review them and publish them as they come along. Let us know your post is part of a planned online book project.

Please ensure that each article or online book chapter follows the same guidelines and rules as any other post that TDS publishes. If you ever decide to sell or exclusively license your book to a third party publisher, you will have to make sure you have their consent to continue to publish the book with TDS. If you do not have such consent, it is your responsibility to remove your content from the TDS publication.

To become a writer, please send your article using our form. Please note that a new author submission process is nearing launch, and this form will be retired upon it’s availability.

We aim to respond to authors as quickly as possible and to let them know whether or not we’ve accepted their articles. On rare occasions, the volume of submissions we receive makes it difficult to respond to everyone; as a general rule, if you haven’t heard from us within a week of submitting your post, it’s safe to assume we won’t move forward with publishing it.

If you’re having an issue with our online form, please let us know via email ([email protected]) so we can help you complete the process. Please do not email us an article that you have already sent via our form.

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