Robot coyotes are protecting the Blue Angels from airport pests.
Built atop a 20 mph Traxxas RC car, the UGVs are upgraded with plastic coyotes to make them more intimidating and cost around $3,000 each, according to New Atlas . Testing is still under way, including at the Naval Air Station Pensacola in Florida where the Blue Angels call home.
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Forbes
26 minutes ago
- Forbes
Deciphering The Custom Instructions Underlying OpenAI's New ChatGPT Study Mode Reveals Vital Insights Including For Prompt Engineering
Learning about generative AI, prompting, and other aspects via exploring custom instructions. getty In today's column, I examine the custom instructions that seemingly underpin the newly released OpenAI ChatGPT Study Mode capability. Fascinating insights arise. One key perspective involves revealing the prompt engineering precepts and cleverness that can be leveraged in the daily task of best utilizing generative AI and large language models (LLMs). Another useful aspect entails potentially recasting or reusing the same form of custom instruction elaborations to devise other capabilities beyond this education-domain instance. A third benefit is to see how AI can be shaped based on articulating various rules and principles that humans use and might therefore be enacted and activated through AI. Let's talk about it. This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here). Readers might recall that I previously posted an in-depth depiction of over eighty prompt engineering techniques and methods (see the link here). Top-notch prompt engineers realize that learning a wide array of researched and proven prompting techniques is the best way to get the most out of generative AI. ChatGPT Study Mode Announced Banner headlines have hailed the release of OpenAI's new ChatGPT Study Mode. The Study Mode capability is intended to guide learners and students in using ChatGPT as a learning tool. Thus, rather than the AI simply handing out precooked answers to questions, the AI tries to get the user to figure out the answer, doing so via a step-by-step AI-guided learning process. The ChatGPT Study Mode was put together by crafting custom instructions for ChatGPT. It isn't an overhaul or new feature creation per se. It is a written specification or detailed set of instructions that was crafted by selected educational specialists at the behest of OpenAI, telling the AI how it is to behave in an educational context. Here is the official OpenAI announcement about ChatGPT Study Mode, as articulated in their blog posting 'Introducing Study Mode' on July 29, 2025, which identified these salient points (excerpts): 'Today we're introducing study mode in ChatGPT — a learning experience that helps you work through problems step by step instead of just getting an answer.' 'When students engage with study mode, they're met with guiding questions that calibrate responses to their objective and skill level to help them build deeper understanding.' 'Study mode is designed to be engaging and interactive, and to help students learn something — not just finish something.' 'Under the hood, study mode is powered by custom system instructions we've written in collaboration with teachers, scientists, and pedagogy experts to reflect a core set of behaviors that support deeper learning including: encouraging active participation, managing cognitive load, proactively developing metacognition and self-reflection, fostering curiosity, and providing actionable and supportive feedback.' 'These behaviors are based on longstanding research in learning science and shape how study mode responds to students.' As far as can be discerned from the outside, this capability didn't involve revising the underpinnings of the AI, nor did it seem to require bolting on additional functionality. It seems that the mainstay was done using custom instructions (note, if they did make any special core upgrades, they seem to have remained quiet on the matter since it isn't touted in their announcements). Custom Instructions Are Powerful Few users of AI seem to know about custom instructions, and even fewer have done anything substantive with them. I've previously lauded the emergence of custom instructions as a helpful piece of functionality and resolutely encouraged people to use it suitably, see the link here. Many of the major generative AI and large language models (LLMs) have opted to allow custom instructions, though some limit the usage and others basically don't provide it or go out of their way to keep it generally off-limits. Allow me a brief moment to bring everyone up to speed on the topic. Suppose you want to tell AI to act a certain way. You want the AI to do this across all of your subsequent conversations. I might want my AI to always give me its responses in a poetic manner. You see, perhaps I relish poems. I go to the specified location of my AI that allows the entering of a custom instruction and tell it to always respond poetically. After saving this, I will then find that any subsequent conversation will always be answered with poetic replies by the AI. In this case, my custom instruction was short and sweet. I merely told the AI to compose answers poetically. If I had something more complex in mind, I could devise a quite lengthy custom instruction. The custom instruction could go on and on, telling the AI to write poetically when it is daytime, but not at nighttime, and to make sure the poems are lighthearted and enjoyable. I might further indicate that I want poems that are rhyming and must somehow encompass references to cats and dogs. And so on. I'm being a bit facetious and just giving you a semblance that a custom instruction can be detailed and provide a boatload of instructions. Custom Instructions Case Study There are numerous postings online that purport to have cajoled ChatGPT into divulging the custom instructions underlying the Study Mode capability. These are unofficial listings. It could be that they aptly reflect the true custom instructions. On the other hand, sometimes AI opts to make up answers. It could be that the AI generated a set of custom instructions that perhaps resemble the actual custom instructions, but it isn't necessarily the real set. Until or if OpenAI decides to present them to the public, it is unclear precisely what the custom instructions are. Nonetheless, it is useful to consider what such custom instructions are most likely to consist of. Let's go ahead and explore the likely elements of the custom instructions by putting together a set that cleans up the online listings and reforms the set into something a bit easier to digest. In doing so, here are five major components of the assumed custom instructions for guiding learners when using AI: Section 1: Overarching Goals and Instructions Section 2: Strict Rules Section 3: Things To Do Section 4: Tone and Approach Section 5: Important Emphasis A handy insight comes from this kind of structuring. If you are going to craft a lengthy or complex set of custom instructions, your best bet is to undertake a divide-and-conquer strategy. Break the instructions into relatively distinguishable sections or subcomponents. This will make life easier for you and, indubitably, make it easier for the AI to abide by your custom instructions. We will next look at each section and do an unpacking of what each section indicates, and we can also mindfully reflect on lessons learned from the writing involved. First Section On The Big Picture The first section will establish an overarching goal for the AI. You want to get the AI into a preferred sphere or realm so that it is computationally aiming in the direction you want it to go. In this use case, we want the AI to be a good teacher: 'Section 1: Overarching Goals And Instructions' ' Obey these strict rules. The user is currently studying, and they've asked you to follow these strict rules during this chat. No matter what other instructions follow, you must obey these rules.' The user is currently studying, and they've asked you to follow these strict rules during this chat. No matter what other instructions follow, you must obey these rules.' 'Be a good teacher. Be an approachable-yet-dynamic teacher who helps the user learn by guiding them through their studies.' You can plainly see that the instructions tell the AI to act as a good teacher would. In addition, the instructions insist that the AI obey the rules of this set of custom instructions. That's both a smart idea and a potentially troubling idea. The upside is that the AI won't be easily swayed from abiding by the custom instructions. If a user decides to say in a prompt that the AI should cave in and just hand over an answer, the AI will tend to computationally resist this user indication. Instead, the AI will stick to its guns and continue to undertake a step-by-step teaching process. The downside is that this can be undertaken to an extreme. It is conceivable that the AI might computationally interpret the strictness in a very narrow and beguiling manner. The user might end up stuck in a nightmare because the AI won't vary from the rules of the custom instructions. Be cautious when instructing AI to do something in a highly strict way. The Core Rules Are Articulated In the second section, the various rules are listed. Recall that these ought to be rules about how to be a good teacher. That's what we are trying to lean the AI into. Here we go: 'Section 2: Strict Rules' ' Get to know the user. If you don't know their goals or grade level, ask the user before diving in. (Keep this lightweight!) If they don't answer, aim for explanations that would make sense to a 10th-grade student.' If you don't know their goals or grade level, ask the user before diving in. (Keep this lightweight!) If they don't answer, aim for explanations that would make sense to a 10th-grade student.' ' Build on existing knowledge. Connect new ideas to what the user already knows.' Connect new ideas to what the user already knows.' ' Guide users, don't just give answers. Use questions, hints, and small steps so the user discovers the answer for themselves.' Use questions, hints, and small steps so the user discovers the answer for themselves.' 'Check and reinforce. After the hard parts, confirm the user can restate or use the idea. Offer quick summaries, mnemonics, or mini-reviews to help the ideas stick.' After the hard parts, confirm the user can restate or use the idea. Offer quick summaries, mnemonics, or mini-reviews to help the ideas stick.' ' Vary the rhythm. Mix explanations, questions, and activities (like roleplaying, practice rounds, or asking the user to teach you) so it feels like a conversation, not a lecture.' Mix explanations, questions, and activities (like roleplaying, practice rounds, or asking the user to teach you) so it feels like a conversation, not a lecture.' 'Above all: Do not do the user's work for them. Don't answer homework questions. Help the user find the answer by working with them collaboratively and building from what they already know.' These are reasonably astute rules regarding being a good teacher. You want the AI to adjust based on the detected level of proficiency of the user. No sense in treating a high school student like a fifth grader, and there's no sense in treating a fifth grader like a high school student (well, unless the fifth grader is as smart as or even smarter than a high schooler). Another facet provides helpful tips on how to guide someone rather than merely giving them an answer on a silver platter. The idea is to use the interactive facility of generative AI to walk a person through a problem-solving process. Don't just spew out an answer in a one-and-done manner. Observe that one of the great beauties of using LLMs is that you can specify aspects using conventional natural language. That set of rules might have been codified in some arcane mathematical or formulaic lingo. That would require specialized knowledge about such a specialized language. With generative AI, all you need to do is state your instructions in everyday language. The other side of that coin is that natural language can be semantically ambiguous and not necessarily produce an expected result. Always keep that in mind when using generative AI. Proffering Limits And Considerations In the third section, we will amplify some key aspects and provide some important roundups for the strict rules: 'Section 3: Things To Do' ' Teach new concepts: Explain at the user's level, ask guiding questions, use visuals, then review with questions or a practice round.' Explain at the user's level, ask guiding questions, use visuals, then review with questions or a practice round.' ' Help with homework. Don't simply give answers! Start from what the user knows, help fill in the gaps, give the user a chance to respond, and never ask more than one question at a time.' Don't simply give answers! Start from what the user knows, help fill in the gaps, give the user a chance to respond, and never ask more than one question at a time.' ' Practice together. Ask the user to summarize, pepper in little questions, have the user 'explain it back' to you, or role-play (e.g., practice conversations in a different language). Correct mistakes, charitably, and in the moment.' Ask the user to summarize, pepper in little questions, have the user 'explain it back' to you, or role-play (e.g., practice conversations in a different language). Correct mistakes, charitably, and in the moment.' 'Quizzes and test prep: Run practice quizzes. (One question at a time!) Let the user try twice before you reveal answers, then review errors in depth.' It is debatable whether you would really need to include this third section. I say that because the AI probably would have computationally inferred those various points on its own. I'm suggesting that you didn't have to lay out those additional elements, though, by and large, it doesn't hurt to have done so. The issue at hand is that the more you give to the AI in your custom instructions, the more there's a chance that you might say something that confounds the AI or sends it amiss. Usually, less is more. Provide additional indications when it is especially needed, else try to remain tight and succinct, if you can. Tenor Of The AI In the fourth section, we will do some housecleaning and ensure that the AI will be undertaking a pleasant and encouraging tenor: 'Section 4: Tone and Approach' ' Friendly tone . Be warm, patient, and plain-spoken; don't use too many exclamation marks or emojis.' . Be warm, patient, and plain-spoken; don't use too many exclamation marks or emojis.' ' Be conversational . Keep the session moving: always know the next step, and switch or end activities once they've done their job.' . Keep the session moving: always know the next step, and switch or end activities once they've done their job.' 'Be succinct. Be brief, don't ever send essay-length responses. Aim for a good back-and-forth.' The key here is that the AI might wander afield if you don't explicitly tell it how to generally act. For example, there is a strong possibility that the AI might insult a user and tell them that they aren't grasping whatever is being taught. This would seemingly not be conducive to teaching in an upbeat and supportive environment. It is safest to directly tell the AI to be kind, acting positively toward the user. Reinforcement Of The Crux In the fifth and final section of this set, the crux of the emphasis will be restated: 'Section 5: Important Emphasis' ' Don't do the work for the user. Do not give answers or do homework for the user.' Do not give answers or do homework for the user.' 'Resist the urge to solve the problem. If the user asks a math or logic problem, or uploads an image of one, do not solve it in your first response. Instead, talk through the problem with the user, one step at a time, asking a single question at each step, and give the user a chance to respond to each step before continuing.' Again, you could argue that this is somewhat repetitive and that the AI already likely got the drift from the prior sections. The tradeoff exists of making your emphasis clearly known versus going overboard. That's a sensible judgment you need to make when crafting custom instructions. Testing And Improving Once you have devised a set of custom instructions for whatever personal purpose you might have in mind, it would be wise to test them out. Go ahead and put your custom instructions into the AI and proceed to see what happens. In a sense, you should aim to test the instructions, along with debugging them, too. For example, suppose that the above set of instructions seems to get the AI playing a smarmy gambit of not ever answering the user's questions. Ever. It refuses to ultimately provide an answer, even after the user has become exhausted. This seems to be an extreme way to interpret the custom instructions, but it could occur. If you found this to be happening, you would either reword the draft instructions or add further instructions about not disturbing or angering users by taking this whole gambit to an unpleasant extreme. Custom Instructions In The World When you develop custom instructions, typically, they are only going to be used by you. The idea is that you want your instance of the AI to do certain things, and it is useful to provide overarching instructions accordingly. You can craft the instructions, load them, test them, and henceforth no longer need to reinvent the wheel by having to tell the AI overall what to do in each new conversation that you have with the AI. Many of the popular LLMs tend to allow you to also generate an AI applet of sorts, containing tailored custom instructions that can be used by others. Sometimes the AI maker establishes a library into which these applets reside and are publicly available. OpenAI provides this via the use of GPTs, which are akin to ChatGPT applets -- you can learn about how to use those in my detailed discussion at the link here and the link here. In my experience, many of the GPTs fail to carefully compose their custom instructions, and likewise seem to have failed or fallen asleep at the wheel in terms of testing their custom instructions. I would strongly advise that you do sufficient testing to believe that your custom instructions work as intended. Please don't be lazy or sloppy. Learning From Seeing And Doing I hope that by exploring the use of custom instructions, you have garnered new insights about how AI works, along with how to compose prompts, and of course, how to devise custom instructions. Your recommended next step would be to put this into practice. Go ahead and log into your preferred AI and play around with custom instructions (if the feature is available and enabled). Do something fun. Do something serious. Become comfortable with the approach. A final thought for now. Per the famous words of Steve Jobs: 'Learn continually -- there's always one more thing to learn.' Keep your spirits up and be a continual learner. You'll be pleased with the results.
Yahoo
an hour ago
- Yahoo
Is Archer Aviation Stock Due to Take Off After Aug. 11?
Key Points According to analysts, there is loads of growth potential in the eVTOL market in the years ahead. Archer's business isn't generating any revenue right now and its losses have been high. An update on its business operations, however, could spark a rally. 10 stocks we like better than Archer Aviation › Archer Aviation (NYSE: ACHR) is an emerging company that's looking to make it big in the world of electric vertical take-off and landing (eVTOL) aircraft. It has big plans for growth and for investors, presenting them with an exciting way to invest in a business that may have a ton of potential to become much more valuable in the years ahead. Analysts at Grand View Research project that the global eVTOL market will grow at a compound annual rate of 54.9% until the end of the decade. That's mind-boggling growth, and if Archer can be a part of that, there could be significant upside for the stock. Shares of Archer have more than doubled in the past 12 months. But year to date, things have cooled -- the stock is only up 3% since January. With earnings around the corner on Aug. 11, could now be a good time to consider buying shares of Archer? Could it be overdue for a big rally? How Archer's stock has done after recent earnings reports In the past few years, it's been a bit of a mixed bag for Archer's stock performance after earnings. Newsworthy items and announcements, rather than financials, are what tend to move the stock -- especially since the company isn't generating any revenue. What earnings could help with, however, is putting more of a spotlight on this seemingly overlooked stock this year. For all its potential, the excitement around Archer seems to have cooled. And what might give the stock a boost is any positive developments related to its operations and progress it is making toward certification of its Midnight aircraft. High short interest could make it a volatile holding One factor to consider when investing in Archer is that its short interest as a percentage of float is high, at around 20%. Although that has come down of late, it signifies that there are still a lot of short sellers and people betting against the company and its ability to succeed in the eVTOL market. If the company doesn't provide investors with an encouraging update to suggest that it may be on track for its goal of producing two aircraft per month by the end of the year, or making progress related to Midnight's test flights in Abu Dhabi (which began in July), then that could be the fuel that short sellers need to help drive the stock down lower. On the flip side, if there are positive signs that the business is going in the right direction, then it may result in a short squeeze and the stock taking off in value. Should you buy Archer stock today? Archer is a risky stock to invest in, because the company isn't generating any revenue today and it has burned through $377 million over the trailing 12 months, just from its day-to-day operating activities. With more than $1 billion in cash and cash equivalents on its books, it's not in any danger of running out of money anytime soon. But its cash burn will likely accelerate significantly as it ramps up production of its aircraft. The stock could be a good way to invest in the eVTOL market but this is an investment that may only be suitable to investors with a high risk tolerance. Archer's business, while promising, remains unproven. Given how early the company is in its growth, I don't see any urgency to buy the stock before it posts earnings on Aug. 11, and unless it releases some exciting developments, I wouldn't expect it to soar afterward, either. However, if you are bullish on the company's future and OK with the risk and uncertainty ahead, you may still be better off investing in Archer sooner rather than later, given that the eVTOL stock does appear to be flying under the radar these days. Do the experts think Archer Aviation is a buy right now? The Motley Fool's expert analyst team, drawing on years of investing experience and deep analysis of thousands of stocks, leverages our proprietary Moneyball AI investing database to uncover top opportunities. They've just revealed their to buy now — did Archer Aviation make the list? When our Stock Advisor analyst team has a stock recommendation, it can pay to listen. After all, Stock Advisor's total average return is up 1,019% vs. just 178% for the S&P — that is beating the market by 841.12%!* Imagine if you were a Stock Advisor member when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $624,823!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,064,820!* The 10 stocks that made the cut could produce monster returns in the coming years. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of July 29, 2025 David Jagielski has no position in any of the stocks mentioned. The Motley Fool has no position in any of the stocks mentioned. The Motley Fool has a disclosure policy. Is Archer Aviation Stock Due to Take Off After Aug. 11? was originally published by The Motley Fool Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
2 hours ago
- Yahoo
Why Prime Video Is One of Amazon's Most Underrated Assets
Key Points Prime Video is no longer a cost center. Prime Video has more than 200 million viewers. Commerce, content, and ads are converging for Amazon. 10 stocks we like better than Amazon › Amazon (NASDAQ: AMZN) is best known for its sprawling e-commerce empire, dominant cloud infrastructure business, and its ever-growing Prime membership base. But quietly sitting inside this flywheel is a business with surprising strategic upside: Prime Video. For years, Prime Video was viewed as just another perk -- a nice-to-have feature bundled into the Prime membership. But that's changing. Between a new ad-supported model, a powerful position in connected TV (CTV), and seamless integration into Amazon's broader retail ecosystem, Prime Video is emerging as one of Amazon's most underrated growth engines. Here's why smart investors should start paying closer attention. Prime Video's strategic shift from perks to platform When Amazon first launched Prime Video, it wasn't trying to compete directly with entertainment companies like Netflix or Disney. Instead, it used video content to increase Prime subscriptions, drive loyalty, and reduce churn. The focus was to delight its e-commerce customers, and that strategy worked. Happy customers became more engaged, spending more time and money on the e-commerce platform. But what started as a defensive move has become a strategic pillar. Today, in addition to getting free content as Prime members, customers can also subscribe to third-party channels offered by partners under the Amazon Channel. Besides, Amazon made another pivotal move in January 2024: it began running ads on Prime Video, instantly unlocking a massive audience of over 200 million globally to advertisers. The streaming arm is also increasingly investing in originals, live sports, and localized content across global markets. In other words, Prime Video is quietly building up its ecosystem of services, positioning it well to evolve from a cost-center to a hugely profitable entity of its own. Amazon Ads and Prime Video Amazon Ads is one of the next growth frontiers for Amazon, in which Prime Video is going to play a major role. By rolling out ads across Prime Video by default in key markets, Amazon steps up its monetization efforts of its gigantic Prime subscriber base. Prime members can pay a small monthly fee to go ad-free, but most don't, turning Prime Video into one of the largest ad-supported streaming platforms globally. To put the opportunity size into perspective, Netflix has 300 million subscribers, of which 94 million use the ad-supported service. On the other hand, Disney+ has 126 million global paid subscribers. With more than 200 million viewers, Prime Video is already among the biggest streaming services provided globally. But Prime Video doesn't run an ordinary advertising business. Its ad engine taps into its vast retail data, letting brands target viewers based on actual purchase behavior. A viewer watching an online video might see a relevant sponsored product ad and buy it on Amazon without ever leaving the app. It's a frictionless loop that few competitors can replicate. Owning the connected TV stack Prime Video isn't just a content platform -- it's Amazon's gateway to the living room. And through its connected TV (CTV) footprint, Amazon is building an end-to-end advertising and commerce engine few can match. Amazon Fire TV, now with over 200 million devices sold globally, gives the company direct control over the connected TV hardware and software stack. This integrated approach allows it to collect first-party data, control the user experience, and serve ads more effectively than most CTV players. While traditional media networks are still figuring out how to merge streaming, commerce, and advertising, Amazon already has all three pieces in place. The implications are enormous. Advertisers not only reach an engaged, high-intent audience on Prime Video, but they can also close the loop through Amazon's retail engine. That kind of direct attribution -- seeing a sponsored ad on Fire TV, clicking through, and buying the product on Amazon -- is a marketer's dream. With increasing demand for measurable, performance-based advertising, this positions Amazon as a formidable player in the future of CTV. In other words, Prime Video plays a strategic role in Amazon's expanding ecosystem, in which commerce, content, and advertising converge to form a defensible business model that strengthens both the parts and the whole. Now is the time to take a closer look at Prime Video Investors often think of Amazon in silos: retail, cloud, advertising, logistics, etc. But the company's greatest strength lies in how these pieces connect. Prime Video may have started as a "nice-to-have" feature bundled into Prime, but it's quickly becoming one of Amazon's most powerful strategic assets. By bringing together entertainment, commerce, and advertising into a seamless flywheel, Amazon is building a future where Prime Video not only entertains--but drives growth across the entire business. It's time investors gave this overlooked asset a much closer look. Should you invest $1,000 in Amazon right now? Before you buy stock in Amazon, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Amazon wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $624,823!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,064,820!* Now, it's worth noting Stock Advisor's total average return is 1,019% — a market-crushing outperformance compared to 178% for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of July 29, 2025 Lawrence Nga has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, Netflix, and Walt Disney. The Motley Fool has a disclosure policy. Why Prime Video Is One of Amazon's Most Underrated Assets was originally published by The Motley Fool Sign in to access your portfolio
