Category Archives: Deep Mind
TADFF 2023: ‘Lovely, Dark, and Deep’ Is Worth Getting Lost In … – Exclaim!
In cinema, forests are often used as a metaphor for the mind a labyrinth of traps impossible to understand, orient ourselves in or escape from, resulting in a daunting place to be alone. Teresa Sutherland's directorial debut, Lovely, Dark, and Deep, takes this theme to its terrifying and inevitable conclusion, using the forest in highly original yet unfortunately inconsistent ways.
A cryptic quote from John Muir appears in the opening frame before we're immediately thrust into the film's forest. Sutherland wastes no time introducing a sinister, isolated tone when a backwoods ranger leaves his post, never to be heard from again.
The film then cuts to Lennon (Georgina Campbell), a newly-minted park ranger stationed in the back country of a national park. Lennon has worked her whole life to reach this coveted position, intent on solving a mystery from her past that's inherently tied to these woods. To reveal any more of the plot would do Sutherland's tense, understated script a disservice.
While Lennon interacts sporadically with a number of people, including fellow park ranger Jackson (Nick Blood) and boss/confidante Zhang (Wai Ching Ho), for the most part she's alone with her thoughts in the woods, placing the weight of the film firmly on Campbell's shoulders. Tough, frightened and determined, Campbell elicits palpable empathy through her performance. She's recently appeared in a number of horrors and thrillers (most notably Barbarian and Bird Box Barcelona) and Campbell has proven herself to be an exceptional talent, primed to become a formidable new scream queen with a modern, more assertive twist.
Long sections of forest exploration pass in near silence an approach that usually leads to some atonal trill, but the ambient sounds of the forest are thankfully treated with respect, heightening the dread. Branko Neskov's intricate sound design makes Lovely, Dark, and Deep feel beautifully realized, filling the screen with cracking tree trunks, rustling vegetation and disembodied voices. Similarly, Rui Poas's lush cinematography feels both intimate and expansive, capturing the grandeur of the forest and Lennon's private moments in her outpost with equal reserve and reverence.
This ability to respect and engage with space is one of the movie's greatest strengths. It understands that the forest is rooted in dichotomy, both delicate and dangerous and large enough to swallow a person whole while feeling entirely claustrophobic. These thoughtful elements build the world into something truly lovely, dark, and deep.
Sutherland, as a writer, is already minted. The Wind is a great but painfully under-seen horror-western, and her work as a staff writer on Mike Flanagan's Midnight Mass, although imperfect, is still inspired. Here, her writing leans towards the latter.
Early on, when Lennon goes on her first deep trek into the forest, she listens to a podcast about missing persons and national parks, which instantly feels leading and unnecessary the cavernous, unforgiving silence reads much more frightening than macabre facts through a pair of headphones. These expository moments prove redundant when coupled with the confident imagery used, and while Sutherland anxiously wants to help us understand the mysteries of this forest, her writing and directorial decisions are strong enough that any hand-holding feels patronizing.
She overuses canted angles, but her ability to create an unsettled mood is vividly on display throughout. A searing slow burn, the film doesn't rely on cheap jump scares or audience manipulation. Instead, it's intent on building a very specific mood and atmosphere through the lead character, with the terror coming from Lennon's memories and trauma, her unsettled inner forest reflecting our own demons. Much like Lennon, we project these monsters onto the forest because, like the deep recesses of our subconscious, it is unknown, dark and isolating a blank canvas for fear.
The film's extended second act features a surreal journey through the past and the mind. Existential horror at its most impressionistic, Lovely, Dark, and Deep adopts some truly disturbing visuals, which happen to also be where some of the film's most glaring problems arise.
Rather than emphasizing the psychological and emotional toll that trauma and isolation can enact the film's strongest and most original aspect Sutherland relies on the forest's mystical elements. It's a trope as well-worn as a pair of old hiking boots: is the mind playing tricks on me or is it the spirits of the forest? This beat grows thin quickly, particularly when the effects on Lennon are depicted with little precedence.
As the story unfolds, there isn't a gradual degradation of the psyche, but rather a harsh left turn that seems to split the film in two. By the time the should-be-harrowing finale arrives, much of the tension that's been building is washed away by dialogue that reveals too much, nullifying the film's hard-won ambiguity and mystique.
People go into the forest to explore, confront fears, find themselves and heal the wounds that fester in more unnatural settings. The forest in Lovely, Dark, and Deep acts as a portal to the past, tunnelling into the deepest recesses of our protagonist's pain where, even in the golden autumnal hue, darkness manifests. The film doesn't just collide with reality; it dismantles it, sending the most frightening message of all: the real danger is in our mind and it's up to us, disoriented and alone, to escape it.
While audiences will inevitably be divided by the film's languid pace, unrealized ambiguity and bottleneck feel, fans of horror that requires patience and empathy will undoubtedly enjoy the sombre mysteries of Lovely, Dark, and Deep a film well worth getting lost in.
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TADFF 2023: 'Lovely, Dark, and Deep' Is Worth Getting Lost In ... - Exclaim!
DeepMind Wants to Use AI to Solve the Climate Crisis – Wired.co.uk
Its a perennial question at WIRED: Tech got us into this mess, can it get us out? Thats particularly true when it comes to climate change. As the weather becomes more extreme and unpredictable, there are hopes that artificial intelligencethat other existential threatmight be part of the solution.
DeepMind, the Google-owned artificial intelligence lab, has been using its AI expertise to tackle the climate change problem in three different ways, as Sims Witherspoon, DeepMinds climate action lead, explained in an interview ahead of her talk at WIRED Impact in London on November 21. This conversation has been edited for clarity and length.
WIRED: How can AI help us tackle climate change?
Sims Witherspoon: There are lots of ways we can slice the answer. AI can help us in mitigation. It can help us in adaptation. It can help us with addressing loss and damage. It can help us in biodiversity and ecology and much more. But I think one of the ways that makes it more tangible for most people is to talk about it through the lens of AIs strengths.
I think of it in three parts: First and foremost, AI can help us understand climate change and the problems that we face related to climate change through better models for prediction and monitoring. One example is our work on precipitation nowcastingso, forecasting rain a few hours aheadand our models were voted more useful and more accurate than other methods by Met Office forecasters, which is great.
But its also just the start because you can then build to predict much more complex phenomena. So AI can be a really significant tool in helping us understand climate change as a problem.
Whats the second thing?
The second bucket that I like to think about is the fact that AI can help us optimize current systems and existing infrastructure. Its not enough to start building new green technology for a more sustainable tomorrow, life needs to go onwe already have many systems that we rely on today, and we cant just burn them all down and start from scratch. We need to be able to optimize those existing systems and infrastructure, and AI is one of the tools that we can use to do this.
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DeepMind Wants to Use AI to Solve the Climate Crisis - Wired.co.uk
Google has sent internet into ‘spiral of decline’, claims DeepMind co … – The Telegraph
Google has plunged the internet into a spiral of decline, the co-founder of the companys artificial intelligence (AI) lab has claimed.
Mustafa Suleyman, the British entrepreneur who co-founded DeepMind, said: The business model that Google had broke the internet.
He said search results had become plagued with clickbait to keep people addicted and absorbed on the page as long as possible.
Information online is buried at the bottom of a lot of verbiage and guff, Mr Suleyman argued, so websites can sell more adverts, fuelled by Googles technology.
Mr Suleyman was one of three people who set up pioneering AI lab DeepMind in London 2010. The company was bought by Google for 400m and it has become the cornerstone of the search giants AI operations.
Mr Suleyman, 39, quit Google 18 months ago and has since set up a rival venture, Inflection AI. The company is developing a conversational chatbot, similar to ChatGPT, amid a race by AI companies to usurp Googles dominance of the web.
The entrepreneur has developed a chatbot called Pi, which he says can act as a kind of AI confidante or coach. He has raised more than $1.5bn for the new technology.
The criticism of his former employer came as Mr Suleyman told the Telegraph about plans for a new international body to monitor AI threats.
Mr Suleyman, along with billionaire former Google chief executive Eric Schmidt, plan to present proposals for an International Panel on AI Safety at Prime Minister Rishi Sunaks global summit on the technology next month.
The DeepMind co-founder said the panel could be modelled on the IPCC the Intergovernmental Panel on Climate Change to establish the scientific consensus around the current capabilities of AI.
Mr Suleyman said the IPCC, which was first set up in 1988, was a good inspiration for establishing a rigorous body for making predictions about AI risks. Other backers of the plan include Reid Hoffman, the billionaire LinkedIn founder, and Florentino Cullar, president of the Carnegie think tank.
The AI panel would provide governments with regular assessments on the level of danger posed by the technology.
The UKs AI Safety Summit is due to take place at Bletchley Park and is expected to gather world leaders and tech entrepreneurs to address the challenges of frontier AI that might cause significant harm, including the loss of life.
The two-day summit on Nov 1 and 2 is expected to be attended by top lobbyists from the likes of Meta and Google. Kamala Harris, the US vice president, is expected to attend, while a Chinese delegation has been invited.
The leaders will try to find common ground on tackling AI risks. Officials are also understood to be considering setting up an international institute for AI safety.
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Google has sent internet into 'spiral of decline', claims DeepMind co ... - The Telegraph
DeepMind Wants to Use AI to Solve the Climate Crisis – WIRED
Its a perennial question at WIRED: Tech got us into this mess, can it get us out? Thats particularly true when it comes to climate change. As the weather becomes more extreme and unpredictable, there are hopes that artificial intelligencethat other existential threatmight be part of the solution.
DeepMind, the Google-owned artificial intelligence lab, has been using its AI expertise to tackle the climate change problem in three different ways, as Sims Witherspoon, DeepMinds climate action lead, explained in an interview ahead of her talk at WIRED Impact in London on November 21. This conversation has been edited for clarity and length.
WIRED: How can AI help us tackle climate change?
Sims Witherspoon: There are lots of ways we can slice the answer. AI can help us in mitigation. It can help us in adaptation. It can help us with addressing loss and damage. It can help us in biodiversity and ecology and much more. But I think one of the ways that makes it more tangible for most people is to talk about it through the lens of AIs strengths.
I think of it in three parts: First and foremost, AI can help us understand climate change and the problems that we face related to climate change through better models for prediction and monitoring. One example is our work on precipitation nowcastingso, forecasting rain a few hours aheadand our models were voted more useful and more accurate than other methods by Met Office forecasters, which is great.
But its also just the start because you can then build to predict much more complex phenomena. So AI can be a really significant tool in helping us understand climate change as a problem.
Whats the second thing?
The second bucket that I like to think about is the fact that AI can help us optimize current systems and existing infrastructure. Its not enough to start building new green technology for a more sustainable tomorrow, life needs to go onwe already have many systems that we rely on today, and we cant just burn them all down and start from scratch. We need to be able to optimize those existing systems and infrastructure, and AI is one of the tools that we can use to do this.
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DeepMind Wants to Use AI to Solve the Climate Crisis - WIRED
POWER OF AI: Wild predictions of power demand from AI put … – S&P Global
The rapid push to adopt artificial intelligence and machine learning in various segments of the energy sector will have far-reaching impacts that are only just starting to be understood. However, the electricity market, which already faces serious challenges from rapid renewables growth and widespread electrification, is expecting some significant net demand gains as a result of the new technology.
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This feature begins to explore some of the main power sector impacts and will be part of a longer series that addresses AI in several important areas of the energy industry.
For access to all installments of the POWER OF AI series, join us on Platts Connect.
The volume of electricity needed for artificial intelligence remains unclear, but it appears the technology will lead to a significant net increase in US power consumption, though some applications could reduce power demand, industry experts told S&P Global Commodity Insights.
"Regarding US power demand, it's really hard to quantify how much demand is needed for things like ChatGPT," David Groarke, managing director at consultant Indigo Advisory Group, said in a recent phone interview. "In terms of macro numbers, by 2030 AI could account for 3% to 4% of global power demand. Google said right now AI is representing 10% to 15% of their power use or 2.3 TWh annually."
However, Google could significantly increase its power demand if generative AI were used in every Google search, according to academic research conducted by Alex de Vries, a PhD candidate at the VU Amsterdam School of Business and Economics.
Citing research by semiconductor analysis firm SemiAnalysis, de Vries in a commentary published Oct. 10 in the journal Joule, estimated that using generative AI such as ChatGPT in each Google search would require more than 500,000 of Nvidia's A100 HGX servers, totaling 4.1 million graphics processing units, or GPUs. At a power demand of 6.5 kW per server, that would result in daily electricity consumption of 80 GWh and annual consumption of 29.2 TWh.
But such widespread adoption with current hardware and software is unlikely due to economic and server supply chain constraints, de Vries said in the commentary. That volume of Nvidia servers does not currently exist, and the cost to produce such a number could run up to $100 billion.
"In summary, while the rapid adoption of AI technology could potentially drastically increase the energy consumption of companies such as Google, there are various resource factors that are likely to prevent such worst-case scenarios from materializing," De Vries said in the commentary.
Close attention to datacenter geography and demand trends will be increasingly important for grid operators as AI adoption progresses.
Power demand from operational and currently planned datacenters in US power markets is expected to total about 30,694 MW once all the planned datacenters are operational, according to analysis of data from 451 Research, which is part of S&P Global Market Intelligence. Investor-owned utilities are set to supply 20,619 MW of that capacity.
To put those numbers into perspective, consider that US Lower 48 power demand is forecast to total about 473 GW in 2023, and rise to about 482 GW in 2027, according to an S&P Global Commodity Insights analytics forecast.
However, those expectations still don't assume any radical adjustments due to adoption of AI.
If significant forecast adjustments need to be made, the earliest indications will likely come from the utilities that serve the big datacenters.
Dominion Energy serves the largest datacenter market in the world in Loudoun County, Virginia, about 30 miles west of Washington, DC. The Richmond, Virginia-headquartered investor-owned utility has pointed out that electricity demand from datacenters in Virginia increased by about 500% from 2013 to 2022.
Since 2019, 81 datacenters with a combined capacity of 3.5 GW have connected to Dominion's power system, the utility said in a late June presentation to Mid-Atlantic grid operator PJM Interconnection.
"From 2023 to 2030, we are looking at about an 80% increase in US data center power demand, going from about 19 GW to about 35 GW," Stephen Oliver, vice president of corporate marketing and investor relations at Navitas Semiconductor, said in an interview.
Initial power demand for training AI is high and is more concentrated than traditional datacenter applications. "A typical rack which consumes 30 kW to 40 kW, with AI processors, like NVIDIA Grace Hopper H100, it's 2x-3x the power in the same rack, so we need new technology in the power converters," Oliver said.
"We see it popping up across the globe and while familiar names like Amazon Web Services, Microsoft and Google operate the data centers themselves, the hardware is designed and built by Taiwan-based companies like Delta, Lite On and Chicony," he said.
"We need to use new technology without taking up space within the cabinets," he said.
It is useful to look at AI in two broad slots, Groarke said, narrow AI that are a little more contained and not that energy intensive, with use cases like load forecasting and predictive maintenance. Secondly, "inference usage" like running a prompt that provides an answer adds to power consumption, along with computing hardware like data centers, he said.
The swath of applications that is really energy intensive is the language learning side, which needs more memory and storage. These are things like neural networks that need thousands of GPUs, he said.
Constance Crozier, assistant professor at Georgia Tech's H. Milton Stewart School of Industrial and Systems Engineering said that training something like ChatGPT uses about 1 billion times the power of running it -- but for end-uses this popular, the aggregate power consumed by running can become significant or even larger.
Power demand for AI comes from training these models which are pulling in "huge amounts of data from the web, and that seems to be doubling every year," Groarke said.
Global data volumes double every few years and untangling that from data center usage is really challenging, he said.
"The intensity of the training of the models is using the most power," Groarke said. "We need new ways of creating those models, and a lot of this power demand is predicated on how AI is adopted," he added.
AI is not on par with power usage from cryptocurrency, "but we could see that as companies adopt large language models," he said.
Many companies are working at embedding large language models in their own networks. Within the large language model industry there is effort to reduce complexity and increase the efficiency of hardware. "There is an awareness of not just building these models for the sake of it," Groarke said.
There are some AI applications that are learning to control systems in ways that will reduce power demand, Crozier said, adding that Google's Deep Mind is going to trial with being able to control room temperatures, and there is a project looking at temperature control of server rooms.
"There are a lot of efficiency gains to be made in building energy efficiency," she said.
"I have seen academic literature for managing data centers and being smarter with how to allocate load to certain servers," Crozier said.
There are control problems that AI could be used to improve in the future, Crozier said, adding that there are also some non-AI methods that could do the same thing, but they are more complicated because they need more extensive modeling.
"There is interest in this area because you can start something, train it, and see if it can better control buildings," Crozier said.
Virtual Power Plants are more about shifting power demand as opposed to reducing it. Electric vehicle charging is another example where demand could be shifted to times when there is a surplus of renewable power supply.
This is also true of AI training algorithms, which can be paused. "I could imagine a situation where we train these algorithms at times when the grid has fewer constraints, although strong economic incentives would be necessary," she said.
There are also "non-sexy things" like building energy efficiency that can be improved, and "there is a lot of low hanging fruit when we think about where this power is going to come from," Crozier said.
A lot of big computers will have the most power demand, with academics and others booking time to use them. They will have higher utilization rates, she said.
AI is very GPU heavy, but other big simulations that are non-AI are also GPU heavy, she said.
Machines are also collocated, so you can't make the distinction between AI and non-AI. "From a GPU standpoint, the big push is for AI, but it's not 100%," Crozier said.
The Massachusetts Institute of Technology and Google did not return requests for comment. Microsoft declined to comment.
S&P Global Commodity Insights reporter Darren Sweeney produces content for distribution on S&P Capital IQ Pro. S&P Global Commodity Insights is a division of S&P Global Inc.
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POWER OF AI: Wild predictions of power demand from AI put ... - S&P Global
Google’s ‘Wartime’ Urgency to Chase ChatGPT Shakes Up Culture – The Information
When staff working on Googles ChatGPT rival, Bard, hear from managers that they need to work at Bard speed, they know it means moving much faster than they were accustomed to in other parts of the company. Legal reviews of new features can start and end in a day. A feature that might have taken a quarter to prepare in the past now gets done in a week.
For a company that gained a reputation for excessive caution, Googles work to expedite Bard, one of its most important initiatives, has startled some staff and invigorated others, people who have worked on the team told me.
Bard launched in March to help Googles billions of users do what OpenAIs ChatGPT can do: semi-automate their software coding, summarize documents and generate new blog posts or marketing copy based on simple prompts, to name a few examples. And when all is said and done, Bard will likely power Assistant, the companys Siri-like voice assistant.
The Bard team has swelled to several hundred people. Meanwhile, ChatGPTdemonstrated by The Informations report last week that OpenAI revenue has quickly risen to a $1.3 billion annual ratehas put pressure on Bard to move quickly.
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Google's 'Wartime' Urgency to Chase ChatGPT Shakes Up Culture - The Information
Moose spotted along I-91 near Windsor Locks as animal activity increases this fall – FOX61 Hartford
WINDSOR LOCKS, Conn. As mating season gets underway for moose, drivers traveling through Connecticut are asked to be cautious of moose near the roadways.
The reminder from the Department of Energy and Environmental Protection (DEEP) comes after a moose was spotted off of Interstate 91 near Exit 40 in Windsor Locks on Tuesday evening.
Moose are more active this time of year to seek new territory to occupy, which makes them more of a public safety concern, according to DEEP. The moose mating, or "rutting," season also started in September.
A car collision involving a moose is 13 times more likely to end in a human death than a crash involving a deer, according to data collected from other states. On impact, moose often end up hitting the windshields, according to DEEP.
Drivers are urged to slow down and look higher than one would when looking for deer since moose stand higher.
Moose are most active at dusk and dawn. It's also infrequent to see the reflection of their eyes from headlights.
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DEEP discourages people from approaching a moose since they can become aggressive and behave unpredictably in populated areas.
All collisions with moose, deer and bears are asked to be reported to local, state or DEEP Environmental Conservation Police (EnCon) officers. Moose sightings near a major highway should also be reported to DEEP EnCon. DEEP's 24-hour dispatch can be reached at 860-424-3333.
To report a general moose sighting to DEEP, visit this survey site.
For general information on moose in Connecticut,click here.
The moose population in Connecticut is small, and there are about 100 individuals in the moose population. Coincidentally, there have been around 100 moose sightings reported in Connecticut so far this season. Click here for an interactive map that shows sighting reports in Connecticut for moose, bears and bobcats.
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Moose spotted along I-91 near Windsor Locks as animal activity increases this fall - FOX61 Hartford
‘France is a bit overhyped’ Nathan Benaich on the state of AI in … – Sifted
2023 is the year that AI went mainstream, stealing the hearts of big tech companies and propelling chipmaker NVIDIA to a trillion-dollar market capitalisation.
And while many of the headlines have focused on the US, there is still a lot to be optimistic about in Europe, according to Air Street Capitals State of AI report. The research shows the UK continues to be a unicorn leader and gives props to UK-based DeepMind, Googles AI arm.
Here are the main takeaways:
While the US and China dwarf Europe when it comes to AI unicorns, the UK boasts more than double the number of billion-dollar valued companies than its closest continental rival.
The country added three AI unicorns this year, bringing the total to 27.
When asked whether France which has seen buzzy new companies like Dust and Mistral spin out of big tech AI labs this year is the sleeping giant of European AI, Air Street founder Nathan Benaich poured a dash of cold water on the hype.
I would say it [France] is probably a bit overhyped. That crew is awesome, but its been around for a while, he tells Sifted.
If I go back and see who were the cool kids doing AI a couple of years ago, compared to who are the cool kids doing it now, it's probably the same people French tech marketing is very good a lot better than the UK for some reason. They have immense public national pride for this stuff.
The report notes London-based Synthesia (an Air Street portfolio company) as one GenAI startup gaining real enterprise traction noting that 44% of Fortune 100 companies use its tech. Benaich also namechecked London-founded ElevenLabs which has raised from VC heavyweight Andreessen Horowitz as another success story.
Air Streets report spotlights breakthrough research from European companies like self-driving car company Wayves GAIA-1 and LINGO-1 models that use both text and visuals to create better autonomous car control, and Google DeepMinds RoboCat model, which can operate 36 robots across 253 tasks.
Benaich argues that companies like these deserve praise for focusing on hard problems, rather than the low-hanging-fruit use cases that companies are applying text and image generation to.
DeepMind didn't really invest all that much attention into chasing OpenAI and doing GPT-style systems because fundamentally, Demis [Hassabis] and the leadership are building a science organisation, he says. Theyre more interested in solving sciences grand challenges than making nice pictures and I have a lot of respect for that.
Former Google DeepMind founders are now increasingly taking their experience from the AI lab and founding their own companies in life sciences, a space that Benaich describes as having a lot of potential.
He also expects good things from Google DeepMinds new multimodal generative model Gemini, which is expected to be released before the end of the year.
They [Google] can compete on this because it doesn't cannibalise their business. They already have a money-printing ads business. So it's quite compelling to be in that position, he says.
The report also notes that there are growing efforts in the AI industry to build more efficient, smaller models something that Paris-based Mistral is focused on and Benaich says there will be room for these cheaper alternatives to the likes of GPT-4.
I do believe in the long tail idea Some open-ended dialogue problems will require a large model, but not every use case needs a general purpose system, he tells Sifted.
The Air Street report also notes how the conversation around AI risk has shed its status as the unloved cousin of AI research, to one thats front and centre of national policy debates today.
Benaich says hes less concerned by existential risks, and more by the threat of misinformation and the impact that products like AI companion apps might have on young people.
If you look at things like developing a new anthrax, you talk to people in biology and theyll tell you that you dont need AGI [artificial general intelligence] for this stuff, he says. Being an AI doomer is like part of the fundraising strategy in a way its the classic thing of: I invented something, its really powerful. It can wreak havoc but it can also reap a lot of benefits. Im the one who can save you.
And while the report notes growing opacity around the research behind powerful AI models from companies like OpenAI and Google, it also highlights the continuing explosion of open source activity. More than 600m AI models were downloaded from AI research platform Hugging Face in August alone, the report points out.
The show right now is still really run by OpenAI, but now youve also got Meta with its Llama models that are really driving open source progress, says Benaich.
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'France is a bit overhyped' Nathan Benaich on the state of AI in ... - Sifted
GOOG Stock: Is Alphabet the First Quadrillion-Dollar Company? – InvestorPlace
Source: PK Studio / Shutterstock
Dont look now, but Alphabets (NASDAQ:GOOG,NASDAQ:GOOGL) shares are nearing 52-week highs. Thats good news for owners of GOOG stock and technology stocks in general. Tech stocks could be back in the saddle.
GOOGs shares are trading within 3% of their 52-week high of $142.38. In the past year, its shares are up nearly 40% and 154% over the past 60 months. Thats almost 3x better than the S&P 500 and 42 percentage points higher than the Nasdaq 100.
Whats especially nice to see if youve opted for GOOG over Apple (NASDAQ:AAPL) stock is that Alphabet is running away from the maker of iPhones as we travel through the years final quarter.
While I like Apple and think it should be in every investors long-term portfolio, Alphabet should be alongside it.
Im no technical analyst, but the fact that Alphabets relative strength index (RSI) has dramatically improved in October it was 44 at the end of September, and now its 66, about 50% higher tells me almost ready to crash through its 2021 highs around $150.
A companys RSI ranges between 0 and 100. However, most investors consider anything over 70 to be overvalued and anything under 30 to be overvalued. As a result, some would say GOOG stock is getting close to overvalued territory.
However, if you follow Investors Business Dailys thoughts on relative strength it takes a stocks performance over the past 52 weeks and compares it to all other stocks to develop a rating for that stock you might not feel as bad because in mid-July its IBD RS rating went over 80.
History reveals that the stocks that go on to make the biggest gains tend to have an RS Rating north of 80 in the early stages of their moves, IBD wrote on July 14.
Since mid-July and IBDs article, GOOG stock is up more than 10%. More could be just around the corner.
Of the 54 analysts that cover Alphabets stock, 45 rated Overweight or an outright Buy, with a $150.92 target price 10% higher than where its currently trading.
When Alphabet reported strong Q2 2023 results at the end of July $21.8 billion in operating income, 12% higher than last year Needham analysts had three reasons to be optimistic about the companys stock:
If the Needham analysts were worried about OpenAIs effect on Alphabet, they had a funny way of showing it, raising their price target by $25 to $140.
YouTubes ad revenue in Q2 was $7.7 billion, 4% higher than Q2 2022 and 15% higher than Q1 2023. Thats important because it reverses three consecutive quarters of slowing growth, demonstrating that YouTubes ad revenue model isnt broken.
New YouTube CEO Neal Mohan, who took on the role in March, said in July that he plans to continue to improve the platforms monetization tools and grow the YouTube creator communities. Alphabet CEO Sundar Pichai also noted that YouTube Shorts are viewed by two billion logged-in users each month, 33% higher than a year ago.
Considering the company only started ads on YouTube Shorts late in 2022, the future revenue stream from this segment of YouTube looks very promising.
On the date of publication, Will Ashworth did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
Will Ashworth has written about investments full-time since 2008. Publications where hes appeared include InvestorPlace, The Motley Fool Canada, Investopedia, Kiplinger, and several others in both the U.S. and Canada. He particularly enjoys creating model portfolios that stand the test of time. He lives in Halifax, Nova Scotia.
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GOOG Stock: Is Alphabet the First Quadrillion-Dollar Company? - InvestorPlace
Announcing Pressoir November Wine Dinners: Dive Deep into Two of Frances Finest Wine Producers – wineindustryadvisor.com
Exclusive Pop-Up Dinners Invite You to Indulge in French Wine & Culture Through Extensive Vintage Tastings at Top New York Restaurants
NEW YORK, OCTOBER 17, 2023 New Yorkers seeking to explore the finest chteaus and domaines of France need go no further than the island of Manhattan toexperience an exquisite vintage collection from two of the countrys finest producers, thanks toPressoir, the team behind the premier French wine festivals La Fte Du Champagne, La Table and La Paule. Tickets are now available for the November schedule of pop-up dinners, each providing wines from rarefied collections and cellars paired with the cuisine of New Yorks finest restaurants for once-in-a-lifetime culinary experiences.
With a passionate mission to transport guests to the vibrant regions of Frances most distinguished wineries, the team behind Pressoir believes that unforgettable experiences happen when the best wines from the finest estates and most talented winemakers are brought together with a dedicated community of wine enthusiasts in a setting infused with generous spirit. With this mission in mind, Pressoir has curated exclusive dinners in collaboration with acclaimed wineries and New Yorks award-winning restaurants.
CHTEAU RAYAS AT LEGACY RECORDS DRAWING ROOM
Thursday, November 9, 6:30-9:30pm
Considered by many to be one of the most elegant wines of Chteauneuf-du-Pape, Chateau Rayas is truly unique. Its famous sandy terrain imparts great finesse in these pure Grenache gems. Join Pressoir for a memorable dinner with the unique opportunity to taste twelve wines from the hallowed estate, with vintages spanning from the past three decades.
DOMAINE LEFLAIVE AT CROWN SHY
Tuesday, November 14, 6:30-9:30pm
Tasting a wine from Domaine Leflaive is always a special moment. But, the opportunity to drink thirteen pristine bottles of the famed Puligny-Montrachet producer will certainly make for an unforgettable experience. The Pressoir team has carefully curated extremely rare wines that include a deep five-vintage vertical of the famed Les Pucelles back to 1989 as well as four vintages of Chevalier Montrachet back to 1983, all from Domaine Leflaive.
Founded by celebrated wine expert Daniel Johnnes, whose influence on the wine and hospitality industry is recognized far and wide,Pressoiris the countrys leading wine organization honoring the Burgundy, Champagne, and Rhne Valley regions. Pressoir originated with the first La Paule event held in the U.S. in 2000, designed to bring the wine and culture of Burgundy to American wine lovers. Since then, the Pressoir team has built an organization that is dedicated to showcasing French wine and culture through a range of events and services. To learn more about Pressoir and its ongoing calendar of exclusive events, visit:https://www.pressoir.wine/.
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Announcing Pressoir November Wine Dinners: Dive Deep into Two of Frances Finest Wine Producers - wineindustryadvisor.com