If you’re wondering what happened to Amazon’s new and improved version of its Alexa voice assistant, you’re not alone. reports that the new Alexa is still stuck in its developmental phase and Amazon has cut off access to its beta phase including its new “Let’s Chat” phase. As a result, a planned late 2024 launch has been pushed back to next year.
The problem seems to be with its large language models (LLMs). The new Alexa is designed to from users but it’s also more likely to fail doing some of the most basic things the old version could do quite easily like create a timer or operate smart lights, according to a follow up report from .
Amazon originally planned to unveil its new version of Alexa AI in October but now the timeline has been extended into next year. (As you might have noticed, October has come and gone.) The original timeline planned to premiere the next evolutionary step in Alexa’s advancement on October 17 but Amazon decided to pivot and used the date to show off its new line of Kindle ereaders. Then in August, news surfaced that the new Alexa would be powered by and come with a monthly subscription fee.
As ChatGPT began to rise in popularity in the summer of 2023, Amazon CEO Andy Jassy wanted to see if Alexa could compete if it had an AI upgrade. Jassy reportedly started peppering Alexa with sports questions “like an ESPN reporter at a playoff press conference” and its answers were “nowhere near perfect.” It even made up a recent game score for Jassy.
Despite this, Alexa passed the good enough stage and Jassy and his fellow executives felt their engineers could build a beta version by the early part of 2024. Unfortunately, Amazon wasn’t able to meet its deadline.
Even with the new deadline, the new Alexa still has a long way to go to fix its problems. Some employees told Bloomberg that the problem outside of Alexa’s innerworkings is with Amazon’s overstuffed management and a lack of “a compelling vision for an AI-powered Alexa.” .
OpenAI is reportedly telling investors that it plans on charging $22 a month to use ChatGPT by the end of the year. The company also plans to aggressively increase the monthly price over the next five years up to $44.
The documents obtained by shows that OpenAI took in $300 million in revenue this August, and expects to make $3.7 billion in sales by the end of the year. Various expenses such as salaries, rent and operational costs will cause the company to lose $5 billion this year.
OpenAI is reportedly circulating the documents the NYT reported on as part of a drive to find new investors to prevent or lessen its financial shortfall. Fortunately, OpenAI is raising money on a $150 billion valuation, and a new round of investments could bring in as much as $7 billion.
OpenAI is also reportedly in the midst of switching from . The business model allows for the removal of any caps on investor returns so they’ll have more room to negotiate for new investors at possibly higher rates.
ChatGPT could get more expensive to use in coming years.
The New York Times, citing internal OpenAI docs, reports that OpenAI is planning to raise the price of individual ChatGPT subscriptions from $20 per month to $22 per month by the end of the year. A steeper increase will come over the next five years; by 2029, OpenAI expects it’ll charge $44 per month for ChatGPT Plus.
The aggressive moves reflect pressure on OpenAI from investors to narrow its losses. While the company’s monthly revenue reached $300 million in August, according to the New York Times, OpenAI expects to lose roughly $5 billion this year. Expenditures like staffing, office rent, and AI training infrastructure are to blame. ChatGPT alone was at one point reportedly costing OpenAI $700,000 per day.
OpenAI could face a blowback if it increases prices too quickly. While ChatGPT has roughly 10 million paying users today, surveys suggest that many believe the current $20-per-month price is too high.
The first time I used SocialAI, I was sure the app was performance art. That was the only logical explanation for why I would willingly sign up to have AI bots named Blaze Fury and Trollington Nefarious, well, troll me.
Even the app’s creator, Michael Sayman, admits that the premise of SocialAI may confuse people. His announcement this week of the app read a little like a generative AI joke: “A private social network where you receive millions of AI-generated comments offering feedback, advice, and reflections.”
But, no, SocialAI is real, if “real” applies to an online universe in which every single person you interact with is a bot.
There’s only one real human in the SocialAI equation. That person is you. The new iOS app is designed to let you post text like you would on Twitter or Threads. An ellipsis appears almost as soon as you do so, indicating that another person is loading up with ammunition, getting ready to fire back. Then, instantaneously, several comments appear, cascading below your post, each and every one of them written by an AI character. In the new new version of the app, just rolled out today, these AIs also talk to each other.
When you first sign up, you’re prompted to choose these AI character archetypes: Do you want to hear from Fans? Trolls? Skeptics? Odd-balls? Doomers? Visionaries? Nerds? Drama Queens? Liberals? Conservatives? Welcome to SocialAI, where Trollita Kafka, Vera D. Nothing, Sunshine Sparkle, Progressive Parker, Derek Dissent, and Professor Debaterson are here to prop you up or tell you why you’re wrong.
Screenshot of the instructions for setting up the Social AI app.
Is SocialAI appalling, an echo chamber taken to its logical extreme? Only if you ignore the truth of modern social media: Our feeds are already filled with bots, tuned by algorithms, and monetized with AI-driven ad systems. As real humans we do the feeding: freely supplying social apps fresh content, baiting trolls, buying stuff. In exchange, we’re amused, and occasionally feel a connection with friends and fans.
Everything comes at a cost, and AI is no different. While ChatGPT and Gemini may be free to use, they require a staggering amount of computational power to operate. And if that wasn’t enough, Big Tech is currently engaged in an arms race to build bigger and better models like GPT-5. Critics argue that this growing demand for powerful — and energy-intensive — hardware will have a devastating impact on climate change. So just how much energy does AI like ChatGPT use and what does this electricity use mean from an environmental perspective? Let’s break it down.
ChatGPT energy consumption: How much electricity does AI need?
Calvin Wankhede / Android Authority
OpenAI’s older GPT-3 large language model required just under 1,300 megawatt hours (MWh) of electricity to train, which is equal to the annual power consumption of about 120 US households. For some context, an average American household consumes just north of 10,000 kilowatt hours each year. That is not all — AI models also need computing power to process each query, which is known as inference. And to achieve that, you need a lot of powerful servers spread across thousands of data centers globally. At the heart of these servers are typically NVIDIA’s H100 chips, which consume 700 watts each and are deployed by the hundreds.
Estimates vary wildly but most researchers agree that ChatGPT alone requires a few hundred MWh every single day. That is enough electricity to power thousands of US households, and maybe even tens of thousands, a year. Given that ChatGPT is no longer the only generative AI player in town, it stands to reason that usage will only grow from here.
AI could use 0.5% of the world’s electricity consumption by 2027.
A paper published in 2023 makes an attempt to calculate just how much electricity the generative AI industry will consume within the next few years. Its author, Alex de Vries, estimates that market leader NVIDIA will ship as many as 1.5 million AI server units by 2027. That would result in AI servers utilizing 85.4 to 134 terawatt hours (TWh) of electricity each year, more than the annual power consumption of smaller countries like the Netherlands, Bangladesh, and Sweden.
While these are certainly alarmingly high figures, it’s worth noting that the total worldwide electricity production was nearly 29,000 TWh just a couple of years ago. In other words, AI servers would account for roughly half a percent of the world’s energy consumption by 2027. Is that still a lot? Yes, but it needs to be judged with some context.
The case for AI’s electricity consumption
AI may consume enough electricity to equal the output of smaller nations, but it is not the only industry to do so. As a matter of fact, data centers that power the rest of the internet consume way more than those dedicated to AI and demand on that front has been growing regardless of new releases like ChatGPT. According to the International Energy Agency, all of the world’s data centers consume 460 TWh today. However, the trendline has been increasing sharply since the Great Recession ended in 2009 — AI had no part to play in this until late 2022.
Even if we consider the researcher’s worst case scenario from above and assume that AI servers will account for 134 TWh of electricity, it will pale in comparison to the world’s overall data center consumption. Netflix alone used enough electricity to power 40,000 US households in 2019, and that number has certainly increased since then, but you don’t see anyone clamoring to end internet streaming as a whole. Air conditioners account for a whopping 10% of global electricity consumption, or 20x as much as AI’s worst 2027 consumption estimate.
AI’s electricity usage pales in comparison to that of global data centers as a whole.
AI’s electricity consumption can also be compared with the controversy surrounding Bitcoin’s energy usage. Much like AI, Bitcoin faced severe criticism for its high electricity consumption, with many labeling it a serious environmental threat. Yet, the financial incentives of mining have driven its adoption in regions with cheaper and renewable energy sources. This is only possible because of the abundance of electricity in such regions, where it might otherwise be underutilized or even wasted. All of this means that we should really be asking about the carbon footprint of AI, and not just focus on the raw electricity consumption figures.
The good news is that like cryptocurrency mining operations, data centers are often strategically built in regions where electricity is either abundant or cheaper to produce. This is why renting a server in Singapore is significantly cheaper than in Chicago.
Google aims to run all of its data centers on 24/7 carbon-free energy by 2030. And according to the company’s 2024 environmental report, 64% of its data centers’ electricity usage already comes from carbon-free energy sources. Microsoft has set a similar target and its Azure data centers power ChatGPT.
Increasing efficiency: Could AI’s electricity demand plateau?
Robert Triggs / Android Authority
As generative AI technology continues to evolve, companies have also been developing smaller and more efficient models. Ever since ChatGPT’s release in late 2022, we’ve seen a slew of models that prioritize efficiency without sacrificing performance. Some of these newer AI models can deliver results comparable to those of their larger predecessors from just a few months ago.
For instance, OpenAI’s recent GPT-4o mini is significantly cheaper than the GPT-3 Turbo it replaces. The company hasn’t divulged efficiency numbers, but the order-of-magnitude reduction in API costs indicates a big reduction in compute costs (and thus, electricity consumption).
We have also seen a push for on-device processing for tasks like summarization and translation that can be achieved by smaller models. While you could argue that the inclusion of new software suites like Galaxy AI still results in increased power consumption on the device itself, the trade-off can be offset by the productivity gains it enables. I, for one, would gladly trade slightly worse battery life for the ability to get real-time translation anywhere in the world. The sheer convenience can make the modest increase in energy consumption worthwhile for many others.
Still, not everyone views AI as a necessary or beneficial development. For some, any additional energy usage is seen as unnecessary or wasteful, and no amount of increased efficiency can change that. Only time will tell if AI is a necessary evil, similar to many other technologies in our lives, or if it’s simply a waste of electricity.
The Tribeca Film Festival will debut five short films made by AI, . The shorts will use OpenAI’s Sora model, which transforms . This is the first time this type of technology will take center stage at the long-running film festival.
“Tribeca is rooted in the foundational belief that storytelling inspires change. Humans need stories to thrive and make sense of our wonderful and broken world,” said co-founder and CEO of Tribeca Enterprises Jane Rosenthal. Who better to chronicle our wonderful and broken world than some lines of code owned by a company that to let CEO Sam Altman and other board members ?
The unnamed filmmakers were all given access to the Sora model, which isn’t yet available to the public, though they have to follow the terms of the agreements negotiated during the recent strikes . OpenAI’s COO, Brad Lightcap, says the feedback provided by these filmmakers will be used to “make Sora a better tool for all creatives.”
When we last covered Sora, it could only handle 60 seconds of video from a single prompt. If that’s still the case, these short films will make Quibi shows look like a Ken Burns documentary. The software also struggles with cause and effect and, well, that’s basically what a story is. However, all of these limitations come from the ancient days of February, and this tech tends to move quickly. Also, I assume there’s no rule against using prompts to create single scenes, which the filmmaker can string together to make a story.
We don’t have that long to find out if cold technology can accurately peer into our warm human hearts. The shorts will screen on June 15 and there’s a conversation with the various filmmakers immediately following the debut.
This follows a spate of agreements between . Vox Media, The Atlantic, News Corp, Dotdash Meredith and even Reddit have all struck deals with OpenAI to let the company train its models on their content. Meanwhile, Meta and Google are looking for to train its models. It looks like we are going to get this “AI creates everything” future, whether we want it or not.
