How AI Could Change the Future of Weather Forecasts
Explainer
Weather forecasting helps industries avert billions in losses from extreme events, and AI could make predictions faster, cheaper and more accurate.
Weather forecasting has gone through incremental but tremendous progress in past decades. By one metric, today's five-day forecast is now as accurate as a three-day forecast was in 2000.
Entire ecosystems rely on weather forecasting, and any improvements — particularly as climate change heightens weather volatility — can help not just individuals to better manage risks, but also entire industries to avert billions in economic losses. In the US alone, an estimated one-third of the economy, or about $3 trillion, is sensitive to the weather and climate.
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Forbes
31 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.
Bloomberg
an hour ago
- Bloomberg
Long Covid Hits UK Economy Harder Than Most Other Countries
Britain's economy is still suffering from long Covid. The unmatched spike in public debt, the 1.2 million extra people on sickness benefits, the record postwar tax burden, the bulging size of the state and — above all — weak economic growth are the lasting symptoms of decisions taken during the pandemic. But some of the harm was purely accidental. 'I will be honest, this was a mistake,' says Tim Leunig, referring to size of the £70 billion ($93.2 billion) furlough program he designed to protect people's jobs and income after the country shut down in March 2020.
Yahoo
an hour ago
- Yahoo
5 states with the highest income tax rates— and 5 with the lowest
It's understandable to feel envious of people who live in states with low or no income taxes. After all, after paying federal taxes, state income taxes take another swipe at your bottom line. But if you're comparing places to live, look at the big picture and consider other local taxes, experts say. Because if state income taxes are really low, you're likely paying higher property or sales taxes to compensate for that. 'Washington State famously has no income tax, but high sales tax, and Oregon is the opposite. So you want to look at the whole picture,' says Heather Liston, a certified financial planner, enrolled agent and principal at Clarity Financial in San Francisco. States with the highest income tax rates That said, there are some states where income taxes take a much bigger bite out of residents' earnings. The states with the highest tax rates are as follows. Keep in mind that some states use a graduated, or progressive, tax system — where income is bunched into chunks, each of which is taxed at a different rate. This list focuses on each state's highest tax rate, also called the marginal tax rate. States with the highest tax rates Top tax rate California 13.3% Hawaii 11% New York 10.9% New Jersey, Washington D.C. 10.75% Oregon 9.9% All of the states (and Washington D.C.) in the list above have graduated, aka progressive, tax systems. In a progressive tax system, your marginal tax rate is the top rate you pay, but your effective, or actual, tax rate is a blend of rates, and is generally lower than your marginal rate. Learn more: Marginal vs. effective tax rate: How they differ and how to calculate each rate Note that a state's top tax rate often only affects the people who make the highest taxable incomes. 'People will think of California, for example, and their highest tax rate is much higher than the average around the country. But that's for high income,' says Alyssum Malone, a CFP® and senior wealth advisor with Focus Partners Wealth in Colorado Springs, Colo. Here are two examples of how California's current tax rates apply to specific situations: A married couple that files jointly with $125,000 in taxable income pays a top rate of 8 percent. A single person with $40,000 in taxable income pays a top rate of 4 percent. And portions of income for all taxpayers in California are taxed at 1 percent and 2 percent. In fact, California has a total of nine different tax brackets. That's the nature of a progressive tax system: Your income is separated into different chunks, each of which is taxed at a different rate. And California's 12.3 percent rate? For a married couple filing jointly, that 12.3% rate applies solely to income above $1,442,628 in 2024. For a single filer, the 12.3 percent applies to income above $721,314 in 2024. States with the lowest income tax rates At the other end of the tax spectrum, nine states have no individual income tax: Alaska, Florida, Nevada, New Hampshire, South Dakota, Tennessee, Texas, Washington and Wyoming. (Washington does tax capital gains income for some high earners.) The states that levy an income tax, but have the lowest rates in the country, are as follows. States with the lowest tax rates (among states that levy an income tax) Top income tax rate North Dakota, Arizona 2.5% Indiana, Louisiana 3% Pennsylvania 3.07% Ohio 3.5% Iowa 3.8% Five of these states have flat tax structures — Arizona, Indiana, Iowa, Louisiana and Pennsylvania — while North Dakota and Ohio have a graduated, or progressive tax structure. Learn more: 2025 tax brackets and federal income tax rates How states tax income States tax your income in different ways: Some states have graduated systems, similar to the federal tax system, in which people with low incomes pay lower tax rates and higher earners pay higher ones. Other states employ a flat tax in which the same rate is applied to each taxpayer, regardless of income. And some states have no income tax at all — often grabbing the attention of Americans interested in holding on to as much of their income as possible. However, states with low or no income taxes often make more of their revenue through sales taxes, property taxes and inheritance taxes, Liston says. For that reason, it's best to consider a place's income taxes in context with all the taxes you'll face when living there. Learn more: 10 states with the highest property taxes, and 10 states with the lowest And even then, what you get for those taxes can be drastically different. 'I'm in California, which has famously high taxes in basically all those areas — high income tax, high sales tax, high property tax. But look at how many people choose to live here anyway,' Liston says. 'Taxes pay for services that matter to us,' she says. If you move to a state with lower taxes but find that the government and services don't meet your needs, you might not be happy with that tradeoff, Liston says. Learn more: These 5 states don't levy sales tax, but watch for other taxes Consider the cost of living Comparing states solely by income tax rates doesn't necessarily give a fair picture of what you'll pay in overall taxes if you live there. There's no free lunch, and states have to pay for services somehow, Malone says. Taxpayers also should consider their earning potential in a particular location to fully understand how a place's taxes will affect their finances. 'Maybe the income that they would make is going to be high enough to overcome a higher tax rate,' Malone says. If you're a retiree or thinking about where you might want to retire someday, also consider what kind of breaks are available. 'A lot of states may have state tax, but then offer tax credits, deductions and incentives for retirees, to motivate retirees to live in the state. So the actual tax they're going to pay varies from the rate that they're seeing if they Googled the tax rate,' Malone says. Learn more: America's best states to retire in 2025: New Hampshire takes the top spot Perhaps a better way to understand how where you live impacts your finances would be to use a cost of living calculator, Malone says. Liston thinks that people often focus too much on taxes, especially when considering where they want to live in retirement. 'What matters are things like, where do your children and grandchildren live? Where can you get a house with no stairs, or whatever else you need for aging in place? What kind of cultural things do you enjoy?' Liston says. 'Tax should be the least of it when you think about where you want to live.' Learn more: State income tax rates: Check your state's rates Sign in to access your portfolio
