Grok’s track record is spotty at best. But even by the very low standards of xAI, its failure in the aftermath of the tragic mass shooting at Bondi Beach in Australia is shocking. The AI chatbot has repeatedly misidentified 43-year-old Ahmed al Ahmed, the man who heroically disarmed one of the shooters, and claimed the verified video of his deed was something else entirely — including that it was an old viral video of a man climbing a tree.
In the aftermath of the attack, Ahmed has been widely praised for his heroism, but some have tried to dismiss or even deny his actions. Someone even quickly whipped up a fake news site that appears to be AI-generated, with an article naming a fictitious IT professional, Edward Crabtree, as the man who disarmed the attacker. This, of course, got picked up by Grok and regurgitated on X.
But Grok also suggested that images of Ahmed were of an Israeli being held hostage by Hamas. And it claimed that video taken at the scene was actually of Currumbin Beach, Australia, during Cyclone Alfred.
Broadly, it seems Grok is having trouble understanding queries today and working out the proper answers. It replied to a question about Oracle’s financial difficulties with a summary of the shooting at Bondi Beach. When asked about the validity of a story about a UK police operation, it first stated today’s date, then coughed up poll numbers for Kamala Harris.
Source link
#Grok #spreading #misinformation #Bondi #Beach #shooting
METR had hoped to provide an update to some groundbreaking research published a few months earlier, in 2025, on AI coding productivity. In it, researchers measured how much time open source developers took to do tasks by hand versus with AI.
While developers in that study reported that AI was making them more productive, they were shocked to learn it actually slowed them down. Sure, it generated code faster, but then they spent extra time finding and fixing errors, steering the AI and waiting on it to complete tasks.
When METR set out to repeat the experiment to measure advances in AI and coder proficiency, they couldn’t.
Devs weren’t willing to participate “because they do not wish to work without AI” even just for the study, the researchers confessed.
Instead, METR published a survey in May that allowed technical employees to self-report their AI productivity gains. Not surprisingly, they perceived that AI made them twice as valuable to their organizations.
Tokenmaxxing, or using the number of tokens a person uses as a proxy for productivity with AI, has been the trend of 2026 so far. And it may already be over.
Amazon shut down its internal token-tracking leaderboard called Kirorank after employees were gaming it by using AI agents excessively, and running up costs, the Financial Times reported this week. The employees proved that AI use does not automatically translate to increased productivity.
Uber blew through its 2026 AI budget within the first four months of the year, The Information reported. COO Andrew Macdonald recently said on a podcast that such spending hadn’t led to a measurable increase in projects or productivity.
AI-generated code also doesn’t necessarily reduce ongoing code maintenance needs, and may even increase it, programmer and author James Shore elegantly argued in a blog post that went viral on Hacker News.
“You write code twice as quick now? Better hope you’ve halved your maintenance costs,” he wrote. “Otherwise, you’re screwed. You’re trading a temporary speed boost for permanent indenture.”
There’s other evidence that AI can increases code maintenance woes.
A viral tweet from Aiswarya Sankar, founder and CEO of reliability engineering agent startup Entelligence AI, proclaims that companies are spending 44% of their tokens on bug fixes that their AI generated. Code reviewing tool company Code Rabbit says it analyzed open source pull requests and found that AI produced 1.7x more problems than human code.
Those are, admittedly, self-serving stats from those trying to sell AI code reviewing tools.
Yet independent researchers have also found such issues. Researchers from the respected Singapore Management University published a report in April warning that “AI-generated code can introduce long-term maintenance costs into real software projects.”
Given that programmers love their AI assistants, what’s the solution?
Well, those who want to sell you AI coding agents say devs can just use AI coding agents to do the bone wearing tasks of fixing code as fast as AI spits it out. That’s what Cognition founder CEO Scott Wu suggests, maker of AI coding agent Devin.
But even he admits that, while Devin can work independently, he’d currently rate its skill between a junior and mid-level programmer, depending on the task. This is not a hand-it-off and forget it solution.
The SMU researchers suggest a more human approach. Programmers should know what tasks AI does and doesn’t do well as deeply as they know their favorite coding languages. They need strong quality assurance systems designed for AI and they are stuck with carefully reviewing the AI’s work as if it was a junior dev.
Meanwhile, the researchers say (and Wu agrees), humans should still be doing the big-picture work like software architecture and security design.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
METR had hoped to provide an update to some groundbreaking research published a few months earlier, in 2025, on AI coding productivity. In it, researchers measured how much time open source developers took to do tasks by hand versus with AI.
While developers in that study reported that AI was making them more productive, they were shocked to learn it actually slowed them down. Sure, it generated code faster, but then they spent extra time finding and fixing errors, steering the AI and waiting on it to complete tasks.
When METR set out to repeat the experiment to measure advances in AI and coder proficiency, they couldn’t.
Devs weren’t willing to participate “because they do not wish to work without AI” even just for the study, the researchers confessed.
Instead, METR published a survey in May that allowed technical employees to self-report their AI productivity gains. Not surprisingly, they perceived that AI made them twice as valuable to their organizations.
Tokenmaxxing, or using the number of tokens a person uses as a proxy for productivity with AI, has been the trend of 2026 so far. And it may already be over.
Amazon shut down its internal token-tracking leaderboard called Kirorank after employees were gaming it by using AI agents excessively, and running up costs, the Financial Times reported this week. The employees proved that AI use does not automatically translate to increased productivity.
Uber blew through its 2026 AI budget within the first four months of the year, The Information reported. COO Andrew Macdonald recently said on a podcast that such spending hadn’t led to a measurable increase in projects or productivity.
AI-generated code also doesn’t necessarily reduce ongoing code maintenance needs, and may even increase it, programmer and author James Shore elegantly argued in a blog post that went viral on Hacker News.
“You write code twice as quick now? Better hope you’ve halved your maintenance costs,” he wrote. “Otherwise, you’re screwed. You’re trading a temporary speed boost for permanent indenture.”
There’s other evidence that AI can increases code maintenance woes.
A viral tweet from Aiswarya Sankar, founder and CEO of reliability engineering agent startup Entelligence AI, proclaims that companies are spending 44% of their tokens on bug fixes that their AI generated. Code reviewing tool company Code Rabbit says it analyzed open source pull requests and found that AI produced 1.7x more problems than human code.
Those are, admittedly, self-serving stats from those trying to sell AI code reviewing tools.
Yet independent researchers have also found such issues. Researchers from the respected Singapore Management University published a report in April warning that “AI-generated code can introduce long-term maintenance costs into real software projects.”
Given that programmers love their AI assistants, what’s the solution?
Well, those who want to sell you AI coding agents say devs can just use AI coding agents to do the bone wearing tasks of fixing code as fast as AI spits it out. That’s what Cognition founder CEO Scott Wu suggests, maker of AI coding agent Devin.
But even he admits that, while Devin can work independently, he’d currently rate its skill between a junior and mid-level programmer, depending on the task. This is not a hand-it-off and forget it solution.
The SMU researchers suggest a more human approach. Programmers should know what tasks AI does and doesn’t do well as deeply as they know their favorite coding languages. They need strong quality assurance systems designed for AI and they are stuck with carefully reviewing the AI’s work as if it was a junior dev.
Meanwhile, the researchers say (and Wu agrees), humans should still be doing the big-picture work like software architecture and security design.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
#Coders #refusing #work #AIand #bite #TechCrunch">Coders are refusing to work without AI — and that could come back to bite them | TechCrunch
In 2026, you cannot snatch AI coding tools out of developers’ vice-grip hands, researchers have discovered.
But while AI is undoubtedly helping coders produce code faster, it may not be producing better code, other researchers warn. And that could cause problems down the road for them.
Specifically, in February 2026, respected AI research lab METR published a surprising revelation: most developers won’t work, even on a limited number of tasks, without AI anymore.
METR had hoped to provide an update to some groundbreaking research published a few months earlier, in 2025, on AI coding productivity. In it, researchers measured how much time open source developers took to do tasks by hand versus with AI.
While developers in that study reported that AI was making them more productive, they were shocked to learn it actually slowed them down. Sure, it generated code faster, but then they spent extra time finding and fixing errors, steering the AI and waiting on it to complete tasks.
When METR set out to repeat the experiment to measure advances in AI and coder proficiency, they couldn’t.
Devs weren’t willing to participate “because they do not wish to work without AI” even just for the study, the researchers confessed.
Instead, METR published a survey in May that allowed technical employees to self-report their AI productivity gains. Not surprisingly, they perceived that AI made them twice as valuable to their organizations.
Tokenmaxxing, or using the number of tokens a person uses as a proxy for productivity with AI, has been the trend of 2026 so far. And it may already be over.
Amazon shut down its internal token-tracking leaderboard called Kirorank after employees were gaming it by using AI agents excessively, and running up costs, the Financial Times reported this week. The employees proved that AI use does not automatically translate to increased productivity.
Uber blew through its 2026 AI budget within the first four months of the year, The Information reported. COO Andrew Macdonald recently said on a podcast that such spending hadn’t led to a measurable increase in projects or productivity.
AI-generated code also doesn’t necessarily reduce ongoing code maintenance needs, and may even increase it, programmer and author James Shore elegantly argued in a blog post that went viral on Hacker News.
“You write code twice as quick now? Better hope you’ve halved your maintenance costs,” he wrote. “Otherwise, you’re screwed. You’re trading a temporary speed boost for permanent indenture.”
There’s other evidence that AI can increases code maintenance woes.
A viral tweet from Aiswarya Sankar, founder and CEO of reliability engineering agent startup Entelligence AI, proclaims that companies are spending 44% of their tokens on bug fixes that their AI generated. Code reviewing tool company Code Rabbit says it analyzed open source pull requests and found that AI produced 1.7x more problems than human code.
Those are, admittedly, self-serving stats from those trying to sell AI code reviewing tools.
Yet independent researchers have also found such issues. Researchers from the respected Singapore Management University published a report in April warning that “AI-generated code can introduce long-term maintenance costs into real software projects.”
Given that programmers love their AI assistants, what’s the solution?
Well, those who want to sell you AI coding agents say devs can just use AI coding agents to do the bone wearing tasks of fixing code as fast as AI spits it out. That’s what Cognition founder CEO Scott Wu suggests, maker of AI coding agent Devin.
But even he admits that, while Devin can work independently, he’d currently rate its skill between a junior and mid-level programmer, depending on the task. This is not a hand-it-off and forget it solution.
The SMU researchers suggest a more human approach. Programmers should know what tasks AI does and doesn’t do well as deeply as they know their favorite coding languages. They need strong quality assurance systems designed for AI and they are stuck with carefully reviewing the AI’s work as if it was a junior dev.
Meanwhile, the researchers say (and Wu agrees), humans should still be doing the big-picture work like software architecture and security design.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
#Coders #refusing #work #AIand #bite #TechCrunch
officially unveiled the Luna Band, a new voice-first wearable designed to help users improve their daily routines through real-time health tracking. Supported by the company’s LifeOS intelligence system, the wearable continuously monitors body signals and transforms them into personalized recommendations. Luna designed the device for people who want smarter support for productivity, recovery, and overall health. The invite-only Drop 1 is expected to begin shipping by the end of July 2026.
Luna Band: Key Highlights
Luna designed the Luna app to make health tracking simpler and more organized by consolidating several wellness features into a single platform. This app integrates features that involve stress management, nutrition, exercise, supplements, and recovery into a single application. Another customization option available to users is creating personal health modules in the app.
The application brings together aspects of stress, diet, fitness, nutritional supplements, and productivity within the app’s micro-apps. Users can also sync third-party devices and other relevant health-related data sources for a more personalized experience.
The company also allows users to create their own health modules in the app rather than relying solely on prebuilt features. Alongside this, Luna highlights its voice-logging feature, which eliminates the need for manual data entry. Users can quickly record meals, workouts, and daily habits through simple voice commands, making health tracking faster.
Luna designed LifeOS as one of its main AI-powered features to simplify health tracking through personalized insights and recommendations. The system continuously studies body signals, lifestyle habits, biomarkers, and health trends to deliver a better understanding of overall wellness. Luna says LifeOS is included with the Luna Band platform.
Price and Availability
Luna has confirmed that the first release of the Luna Band, called Drop 1, will be available through an invite-only system. Users interested in the wearable can sign up through the company’s official waitlist before shipping starts later in July 2026.
officially unveiled the Luna Band, a new voice-first wearable designed to help users improve their daily routines through real-time health tracking. Supported by the company’s LifeOS intelligence system, the wearable continuously monitors body signals and transforms them into personalized recommendations. Luna designed the device for people who want smarter support for productivity, recovery, and overall health. The invite-only Drop 1 is expected to begin shipping by the end of July 2026.
Luna Band: Key Highlights
Luna designed the Luna app to make health tracking simpler and more organized by consolidating several wellness features into a single platform. This app integrates features that involve stress management, nutrition, exercise, supplements, and recovery into a single application. Another customization option available to users is creating personal health modules in the app.
The application brings together aspects of stress, diet, fitness, nutritional supplements, and productivity within the app’s micro-apps. Users can also sync third-party devices and other relevant health-related data sources for a more personalized experience.
The company also allows users to create their own health modules in the app rather than relying solely on prebuilt features. Alongside this, Luna highlights its voice-logging feature, which eliminates the need for manual data entry. Users can quickly record meals, workouts, and daily habits through simple voice commands, making health tracking faster.
Luna designed LifeOS as one of its main AI-powered features to simplify health tracking through personalized insights and recommendations. The system continuously studies body signals, lifestyle habits, biomarkers, and health trends to deliver a better understanding of overall wellness. Luna says LifeOS is included with the Luna Band platform.
Price and Availability
Luna has confirmed that the first release of the Luna Band, called Drop 1, will be available through an invite-only system. Users interested in the wearable can sign up through the company’s official waitlist before shipping starts later in July 2026.
#Luna #Introduces #Luna #Band #RealTime #Health #Tracking #FeaturesLuna">Luna Introduces Luna Band With Real-Time Health Tracking Features
Luna has officially unveiled the Luna Band, a new voice-first wearable designed to help users improve their daily routines through real-time health tracking. Supported by the company’s LifeOS intelligence system, the wearable continuously monitors body signals and transforms them into personalized recommendations. Luna designed the device for people who want smarter support for productivity, recovery, and overall health. The invite-only Drop 1 is expected to begin shipping by the end of July 2026.
Luna Band: Key Highlights
Luna designed the Luna app to make health tracking simpler and more organized by consolidating several wellness features into a single platform. This app integrates features that involve stress management, nutrition, exercise, supplements, and recovery into a single application. Another customization option available to users is creating personal health modules in the app.
The application brings together aspects of stress, diet, fitness, nutritional supplements, and productivity within the app’s micro-apps. Users can also sync third-party devices and other relevant health-related data sources for a more personalized experience.
The company also allows users to create their own health modules in the app rather than relying solely on prebuilt features. Alongside this, Luna highlights its voice-logging feature, which eliminates the need for manual data entry. Users can quickly record meals, workouts, and daily habits through simple voice commands, making health tracking faster.
Luna designed LifeOS as one of its main AI-powered features to simplify health tracking through personalized insights and recommendations. The system continuously studies body signals, lifestyle habits, biomarkers, and health trends to deliver a better understanding of overall wellness. Luna says LifeOS is included with the Luna Band platform.
Price and Availability
Luna has confirmed that the first release of the Luna Band, called Drop 1, will be available through an invite-only system. Users interested in the wearable can sign up through the company’s official waitlist before shipping starts later in July 2026.
There are other similar studies underway, including in the United States. Some are testing semaglutide for other kinds of substance use disorder, like opioids. Others are testing newer drugs like tirzepatide (a dual agonist that pairs GLP-1 with the hunger-related hormone GIP).
I reached out to an outside expert, Asim Shah, a professor and executive vice chair of psychiatry and behavioral sciences at Baylor College of Medicine, to talk about the emerging science surrounding GLP-1s and addiction treatment. We discussed the leading theory behind why GLP-1s can reduce addiction, his opinion of the recent Lancet trial, and what it will take for these drugs to be widely adopted as treatments for substance use disorders. The following has been lightly edited for clarity and grammar.
Ed Cara, Gizmodo: Do we have any sort of sense yet as to how or why GLP-1s seem to be working well against substance use disorders?
Asim Shah: So the craving, or pleasure, center of the brain is related to dopamine, which is a brain neurotransmitter. Whenever you crave something and you eat it or you take it, that gives you pleasure. That is the dopamine functioning in the brain. And all of this is related to the same thing, whether it’s a craving for food, craving for smoking, craving for alcohol, any drug. That’s the neurobiological mechanism of craving and pleasure, and it’s all the same mechanism.
And incidentally, we found out that the people who were losing weight on these GLP-1s, they often also stopped smoking cigarettes and their addiction got better with alcohol. It was an incidental finding, but it’s something people are now trying to study more closely.
Gizmodo: Speaking of studies, what do you make of the newest trial published in The Lancet this month?
Shah: So this was a 26 week study, which had about 100 patients, half and half men and women both. In our world, 100 patients is a medium sized study; a larger one might usually have 300, 400, 600 patients. So this is a medium sized study, which is decent. It’s not bad. And in my opinion, it was done pretty well, not a lot of bias in the study that I saw.
Now, of course, this is not a definitive study. And you need to follow up with these patients after the weeks of study. We call these start-up studies, and they are what we base future, longer and bigger studies on. So it’s a good base, and there are other studies on the way.
Gizmodo: Broadly speaking, what are the questions that these longer and larger studies need to try answering?
Shah: So there are a couple of things.
These are different substances that people are looking at; one is alcohol, one smoking, the other is opiates. So the next studies we should be doing is to see whether GLP-1s like semaglutide can limit more than one of these addictions. Because the mechanism is the same mechanism for all the cravings and the addictions. So can it reduce all of these or just one if somebody is taking it?
If we do keep seeing an effect here, it’s also important to know how quickly this happens and whether it can be sustained after you stop using a GLP-1. That’s why we have to follow people after these sorts of trials, to see if the effect can last after they stop taking the medication or if it requires people needing to stay on the drug for the effect.
Gizmodo: These sort of studies are happening. But what should be the current takeaway for people with these addictions and their doctor? Is this something that could be used in the real world right now?
Shah: Because they’re not approved right now, the takeaway should be that if you already have a current indication to take a GLP-1 which is for diabetes or obesity, certainly take it. If you also get an added advantage of stopping your smoking or alcohol use disorder, that is well and good because we don’t have approval for these disorders currently.
So in other words, if somebody comes to us and says, “Hey, I want to start these medicines for smoking cessation or alcohol use disorder,” we may not be able to prescribe it because there’s no approval. But they can be part of a study which is going on in some centers for those disorders. And if somebody already is using them for diabetes or so, and in addition, they get a benefit for alcoholism, that’s great, too.
There are other similar studies underway, including in the United States. Some are testing semaglutide for other kinds of substance use disorder, like opioids. Others are testing newer drugs like tirzepatide (a dual agonist that pairs GLP-1 with the hunger-related hormone GIP).
I reached out to an outside expert, Asim Shah, a professor and executive vice chair of psychiatry and behavioral sciences at Baylor College of Medicine, to talk about the emerging science surrounding GLP-1s and addiction treatment. We discussed the leading theory behind why GLP-1s can reduce addiction, his opinion of the recent Lancet trial, and what it will take for these drugs to be widely adopted as treatments for substance use disorders. The following has been lightly edited for clarity and grammar.
Ed Cara, Gizmodo: Do we have any sort of sense yet as to how or why GLP-1s seem to be working well against substance use disorders?
Asim Shah: So the craving, or pleasure, center of the brain is related to dopamine, which is a brain neurotransmitter. Whenever you crave something and you eat it or you take it, that gives you pleasure. That is the dopamine functioning in the brain. And all of this is related to the same thing, whether it’s a craving for food, craving for smoking, craving for alcohol, any drug. That’s the neurobiological mechanism of craving and pleasure, and it’s all the same mechanism.
And incidentally, we found out that the people who were losing weight on these GLP-1s, they often also stopped smoking cigarettes and their addiction got better with alcohol. It was an incidental finding, but it’s something people are now trying to study more closely.
Gizmodo: Speaking of studies, what do you make of the newest trial published in The Lancet this month?
Shah: So this was a 26 week study, which had about 100 patients, half and half men and women both. In our world, 100 patients is a medium sized study; a larger one might usually have 300, 400, 600 patients. So this is a medium sized study, which is decent. It’s not bad. And in my opinion, it was done pretty well, not a lot of bias in the study that I saw.
Now, of course, this is not a definitive study. And you need to follow up with these patients after the weeks of study. We call these start-up studies, and they are what we base future, longer and bigger studies on. So it’s a good base, and there are other studies on the way.
Gizmodo: Broadly speaking, what are the questions that these longer and larger studies need to try answering?
Shah: So there are a couple of things.
These are different substances that people are looking at; one is alcohol, one smoking, the other is opiates. So the next studies we should be doing is to see whether GLP-1s like semaglutide can limit more than one of these addictions. Because the mechanism is the same mechanism for all the cravings and the addictions. So can it reduce all of these or just one if somebody is taking it?
If we do keep seeing an effect here, it’s also important to know how quickly this happens and whether it can be sustained after you stop using a GLP-1. That’s why we have to follow people after these sorts of trials, to see if the effect can last after they stop taking the medication or if it requires people needing to stay on the drug for the effect.
Gizmodo: These sort of studies are happening. But what should be the current takeaway for people with these addictions and their doctor? Is this something that could be used in the real world right now?
Shah: Because they’re not approved right now, the takeaway should be that if you already have a current indication to take a GLP-1 which is for diabetes or obesity, certainly take it. If you also get an added advantage of stopping your smoking or alcohol use disorder, that is well and good because we don’t have approval for these disorders currently.
So in other words, if somebody comes to us and says, “Hey, I want to start these medicines for smoking cessation or alcohol use disorder,” we may not be able to prescribe it because there’s no approval. But they can be part of a study which is going on in some centers for those disorders. And if somebody already is using them for diabetes or so, and in addition, they get a benefit for alcoholism, that’s great, too.
#Ozempic #Treat #Alcoholism #Heresaddiction,Alcoholism,GLP-1s,Ozempic,Q&As">Can Ozempic Treat Alcoholism? Here’s What You Should Know
Semaglutide (the active ingredient in Ozempic and Wegovy) and other GLP-1 medications have rapidly become some of the most popular drugs in the world. Originally developed for type 2 diabetes, GLP-1s are now better known for treating obesity. In the near future, though, these drugs could have yet another vital use as treatments for alcohol addiction and other substance use disorders.
Over the past few years, a growing base of evidence has suggested that GLP-1s can tamp down people’s unhealthy urges for alcohol, cocaine, and even vices like gambling. And earlier this month, researchers in Denmark published data from the first double-blinded, randomized, and placebo-controlled trial of semaglutide for alcohol use disorder in The Lancet. Over a 26-week period, the study found that people on semaglutide consumed less alcohol than those given a placebo and experienced noticeably fewer heavy drinking days when they did drink.
There are other similar studies underway, including in the United States. Some are testing semaglutide for other kinds of substance use disorder, like opioids. Others are testing newer drugs like tirzepatide (a dual agonist that pairs GLP-1 with the hunger-related hormone GIP).
I reached out to an outside expert, Asim Shah, a professor and executive vice chair of psychiatry and behavioral sciences at Baylor College of Medicine, to talk about the emerging science surrounding GLP-1s and addiction treatment. We discussed the leading theory behind why GLP-1s can reduce addiction, his opinion of the recent Lancet trial, and what it will take for these drugs to be widely adopted as treatments for substance use disorders. The following has been lightly edited for clarity and grammar.
Ed Cara, Gizmodo: Do we have any sort of sense yet as to how or why GLP-1s seem to be working well against substance use disorders?
Asim Shah: So the craving, or pleasure, center of the brain is related to dopamine, which is a brain neurotransmitter. Whenever you crave something and you eat it or you take it, that gives you pleasure. That is the dopamine functioning in the brain. And all of this is related to the same thing, whether it’s a craving for food, craving for smoking, craving for alcohol, any drug. That’s the neurobiological mechanism of craving and pleasure, and it’s all the same mechanism.
And incidentally, we found out that the people who were losing weight on these GLP-1s, they often also stopped smoking cigarettes and their addiction got better with alcohol. It was an incidental finding, but it’s something people are now trying to study more closely.
Gizmodo: Speaking of studies, what do you make of the newest trial published in The Lancet this month?
Shah: So this was a 26 week study, which had about 100 patients, half and half men and women both. In our world, 100 patients is a medium sized study; a larger one might usually have 300, 400, 600 patients. So this is a medium sized study, which is decent. It’s not bad. And in my opinion, it was done pretty well, not a lot of bias in the study that I saw.
Now, of course, this is not a definitive study. And you need to follow up with these patients after the weeks of study. We call these start-up studies, and they are what we base future, longer and bigger studies on. So it’s a good base, and there are other studies on the way.
Gizmodo: Broadly speaking, what are the questions that these longer and larger studies need to try answering?
Shah: So there are a couple of things.
These are different substances that people are looking at; one is alcohol, one smoking, the other is opiates. So the next studies we should be doing is to see whether GLP-1s like semaglutide can limit more than one of these addictions. Because the mechanism is the same mechanism for all the cravings and the addictions. So can it reduce all of these or just one if somebody is taking it?
If we do keep seeing an effect here, it’s also important to know how quickly this happens and whether it can be sustained after you stop using a GLP-1. That’s why we have to follow people after these sorts of trials, to see if the effect can last after they stop taking the medication or if it requires people needing to stay on the drug for the effect.
Gizmodo: These sort of studies are happening. But what should be the current takeaway for people with these addictions and their doctor? Is this something that could be used in the real world right now?
Shah: Because they’re not approved right now, the takeaway should be that if you already have a current indication to take a GLP-1 which is for diabetes or obesity, certainly take it. If you also get an added advantage of stopping your smoking or alcohol use disorder, that is well and good because we don’t have approval for these disorders currently.
So in other words, if somebody comes to us and says, “Hey, I want to start these medicines for smoking cessation or alcohol use disorder,” we may not be able to prescribe it because there’s no approval. But they can be part of a study which is going on in some centers for those disorders. And if somebody already is using them for diabetes or so, and in addition, they get a benefit for alcoholism, that’s great, too.
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