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Showing posts tagged with: openai

“Distillation” Is Shaking Up The AI Industry

jerry9789
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artificial intelligence, Brandview World

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Copyright: Airam Dato-on

 

Paradigm Shift

We’ve recently written about recent AI advancements and popularity, particularly generative AI like that of ChatGPT, driving renewed demand for data centers not seen in decades.  This surging demand pushed tech investors to put $39.6 billion into data center development in 2024, which is 12 times the amount invested back in 2016.

A recent development, however, has stirred things up, especially the concept that billions of dollars needed to be spent for AI advancement.  Developed by a Chinese AI research lab, an open-source large language model named DeepSeek was released and performed on par with OpenAI, but it reportedly operates for just a fraction of the cost of Western AI models.  OpenAI, however, is investigating if DeepSeek utilized distillation of the former’s AI models to develop their systems.

Copyright: cottonbro studio

 

What Is “Distillation?”

According to Labelbox, model distillation (or knowledge distillation) is a machine learning technique involving the transfer of knowledge from a large model to a smaller one.  Distillation bridges the gap between computational demand and the cost for training large models while maintaining performance.  Basically, the large model learns from an enormous amount of raw data for a number of months and a huge sum of money typically in a training lab, then passes on that knowledge to its smaller counterpart primed for real-world application and production for less time and money.  

Distillation has been around for some time and has been used by AI developers, but not to the same degree of success as DeepSeek.  The Chinese AI developer had said that aside from their own models, they also distilled from open-source AIs released by Meta Platforms and Alibaba.

However, the terms of service for OpenAI prohibits the use of its models for developing competing applications.  While OpenAI had banned suspected accounts for distillation during its investigation, US President Donald Trump’s AI czar David Sacks had called out DeepSeek for distilling from OpenAI models.  Sacks added that US AI companies should take measures to protect their models or make it difficult for their models to be distilled.

Copyright: Darlene Anderson

 

How Does Distillation Affect AI Investments?

On the back of DeepSeek’s success, distillation might give tech giants cause to reexamine their business models and investors to question the amount of dollars they put into AI advancements.  Is it worth it to be a pioneer or industry leader when the same efforts can be replicated by smaller rivals at less cost?  Can an advantage still exist for tech companies that ask for huge investments to blaze a trail when others are too quick to follow and build upon the leader’s achievements?

A recent Wall Street Journal article notes that tech executives expect distillation to produce more high-quality models.  The same article mentions Anthropic CEO Dario Amodei blogging that DeepSeek’s R1 model “is not a unique breakthrough or something that fundamentally changes the economics” of advanced AI systems.  This is an expected development as the costs for AI operations continue to fall and models move towards being more open-source.  

Perhaps that’s where the advantage for tech leaders and investors lies: the opportunity to break new ground and the understanding that you’re seeking answers from unexplored spaces while the rest limit themselves and reiterate within the same technological confines.  Established tech giants continue to enjoy the prestige of their AI models being more widely used in Silicon Valley — despite DeepSeek’s economical advantage — and the expectation of being the first to bring new advancements and developments to the digital world.

And maybe, just maybe, in that space between the pursuit of new AI breakthroughs and lower-cost AI models lie solutions to help meet the increasing demand for data centers and computing power.   

Copyright: panumas nikhomkhai

 

Featured Image Copyright: Matheus Bertelli
Top Image Copyright: Airam Dato-on

 

 

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The Emerging Consensus On AI

jerry9789
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artificial intelligence, Burning Questions

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The Future Is Here

“Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

 

With just 22 words, we are ushered into a future once heralded in science fiction movies and literature of the past, a future our collective consciousness anticipated but has now taken us by surprise upon the realization of our unreadiness.  It is a future where machines are intelligent enough to replicate a growing number of significant and specialized tasks.   A future where machines are intelligent enough to not only threaten to replace the human workforce but humanity itself.

 

Published by the San Francisco-based Center for AI Safety, this 22-word statement was co-signed by leading tech figures such as Google DeepMind CEO Demis Hassabis and OpenAI CEO Sam Altman.  Both have also expressed calls for caution before, joining the ranks of other tech specialists and executives like Elon Musk and Steve Wozniak.

 

Earlier in the year, Musk, Wozniak, and other tech leaders and experts endorsed an open letter proposing a six-month halt on AI research and development.  The suggested pause is presumed to allow for time to determine and implement AI safety standards and protocols.

 

Max Tegmark, physicist and AI researcher at the Massachusetts Institute of Technology and co-founder of the Future of Life Institute, once held an optimistic view of the possibilities granted by AI but has now recently issued a warning.  He remarked that humanity is failing this new technology’s challenge by rushing into the development and release of AI systems that aren’t fully understood or completely regulated.

 

Henry Kissinger himself co-wrote a book on the topic.  In The Age of AI, Kissinger warned us about AI eventually becoming capable of making conclusions and decisions no human is able to consider or understand.  This is a notion made more unsettling when taken into the context of everyday life and warfare.

 

Working With AI

We at Cascade Strategies wholeheartedly agree with this now emerging consensus and additionally, we believe that we’ve been obedient in upholding the responsible and conscientious use of AI.  Not only have we long been advocating for the “Appropriate Use” of AI, but we’ve also made it a hallmark of how we find solutions for our client’s needs with market research and brand management.

 

Just consider the work we’ve done with the Expedia Group.   For years, they’ve utilized a segmentation model to engage with their lodging partners by offering advice that could lead to the partner winning a booking over a competitor.  AI filters through the thousands of possible recommendations to arrive at a shortlist of the best selections optimized for revenue.

 

With the continued growth and diversification of their partners, they then needed a more effective approach in engaging and appealing to them, something that focuses more on that associate’s behavior and motivations.  We came up with two things for Expedia: a psychographic segmentation formed into subgroups based on patterns of thinking, feeling, and perceiving to explain and predict behavior, and more importantly, a Scenario Analyzer that utilizes the underlying AI model but now delivers recommendations in very action-oriented and compelling messaging tailor-fit for that specific partner.

 

The best part about the Scenario Analyzer is whether the partner follows any of the advice recommended or does nothing, Expedia still stands to make a profit while maintaining an image of personalized attentiveness to their partner’s needs.  And ultimately, it’s the partner who gets to decide, not the AI.

Copyright Tara Winstead

 

Our Future With AI

This is how we view and approach AI- it’s not the end-all, be-all solution but rather an essential tool in increasing productivity and efficiency in tandem with excellent human thinking, judgment, and creativity.  Yes, it is going to be part of our future but in line with the new consensus, we believe that AI shaped by human values and experience is the way to go with this emerging and exciting technology.

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What To Make Of ChatGPT’s User Growth Decline

jerry9789
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artificial intelligence, Burning Questions, Uncategorized

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The Beginning Of The End?

More than six months after launching on November 2022, ChatGPT recorded its first decline in user growth and traffic in June 2023.  Spiceworks reported that the Washington Post surmised quality issues and summer breaks from schools could have been factors in the decline, aside from multiple companies banning employees from using ChatGPT professionally.

Brad Rudisail, another Spiceworks writer, opined that a subset of curious visitors driven by the hype over ChatGPT could’ve also boosted the numbers of early visits, the dwindling user growth resulting from the said group moving on to the next talk of the town.

The same article also brings up open-source AI gaining ground on OpenAI’s territory as a possible factor, thanks to customizable, faster, and more useful models on top of being more transparent and the decreased likelihood of cognitive biases.

Don’t Buy Into The Hype

But perhaps the best takeaway is Mr. Rudisail’s point that we’re still in the early stages of AI and it’s premature to herald ChatGPT’s downfall with a weak signal like decreased user growth.  For all we know, this is what could be considered normal numbers, with earlier figures inflated by the excitement surrounding its launch.  Don’t buy into the hype is a position we at Cascade Strategies advocate when it comes to matters of AI.

 

The advent of AI has taken productivity and efficiency to levels never seen before, so the initial hoopla over it is understandable.  However, we believe people are now starting to become a little more settled in their appraisal of AI.  They’re starting to see that AI is pretty good at “middle functions” requiring intelligence, whether that be human or machine-based.  But when it comes to “higher function” tasks which involve discernment, abstraction and creativity, AI output falls short of excellence.  Sometimes mediocrity is acceptable, but for most pursuits excellence is needed.

 

Excellence Achieved Through High Level Human Thinking

To illustrate just how AI would come out lacking in certain activities, let’s consider our case study for the Gargoyles brand of sunglasses.  ChatGPT can produce a large number of ads for sunglasses at little or no cost, but most of those ads won’t bring anything new to the table or resonate with the audience.

However, when researchers spent time with the most loyal customers of Gargoyles to come up with a new ad, they discovered a commonality that AI simply did not have the power to discern.  They found a unique quality of indomitability among these brand loyalists: many of them had been struck down somewhere in their upward striving, and they found the strength and resolve to keep going while the odds were clearly against them.  They kept going and prevailed.  The researchers were tireless in their pursuit of this rare trait, and they stretched the interpretive, intuitive, and synthesis-building capacities of their right brains to find it.  Stretching further, they inspired creative teams to produce the award-winning “storyline of life” campaign for the Gargoyles brand.

All told, this is a story of seeking excellence, where hard-working humans press the ordinary capacities of their intellects to higher layers of understanding of a subject matter, not settling for simply a summarization of the aggregate human experience on the topic.  This is what excellence is all about, and AI is not prepared to do it.  To achieve it, humans have to have a strong desire to go beyond the mediocre.  They have to believe that stretching their brains to this level results in something good.

 

How To Make “Appropriate Use” of AI

But that is not to say that AI and high level human thinking can’t mix.  The key is to recognize where AI would best fit in your process and methodologies, then decide where human intervention comes in.  This is what we call “Appropriate Use” of AI.

 

Take for example our case study for Expedia Group and how they engage with millions of hospitality partners.  Expedia offers their partner “advice” which helps them receive a booking over their competitors.  With thousands of pieces of advice to give their partners, they utilize AI to filter through all those recommendations and present only the best ones to optimize revenue.  Cascade Strategies has helped them further by creating a tool called Scenario Analyzer, which uses the underlying AI model to automate the selection of these most revenue-optimal pieces of advice.

 

Either way, the end decision on which advice to go with (or whether they accept any advice at all) ultimately still comes from Expedia’s partner, not the AI.

Copyright ClaudeAI.uk

 

A Double-edged Sword

As you can see with ChatGPT, it’s easy to get carried away with all the hype surrounding AI.  At launch, it was acclaimed for the exciting possibilities it represented, but now that it has hit a bump in the road, some people and outlets act as if ChatGPT is on its last leg.  Hype is good when it’s necessary to draw attention; unfortunately in most cases, it sets up the loftiest of expectations when good sense gets overridden.

 

This is why we think a sensible mindset is the best way to approach and think about AI — to see it for what it really is.  It’s a tool for increasing productivity and efficiency, not the end-all and be-all, as there is still much room for excellent human thinking backed by experience and values to come into play.  Our concerns for now may not be as profound and dire as those expressed by James Cameron, Elon Musk, Steve Wozniak and others, but we’d like to believe that “appropriate use” of AI is the key towards better understanding and responsible stewardship of this emerging new technology.

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A highly innovative, award-winning market research and consulting firm with over 31 years’ experience in the field. Cascade provides consistent excellence in not only the traditional methodologies such as mobile surveys and focus groups, but also in cutting-edge disciplines like Predictive Analytics, Deep Learning, Neuroscience, Biometrics, Eye Tracking, Virtual Reality, and Gamification.
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