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ChatGPT VS DeepSeek: Will DeepSeek Dethrone ChatGPT?
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Jan 28, 2025
What is going on in the Artificial Intelligence Industry right now truly demands your attention. Deepseek, a Chinese-owned AI company just became the number 1 downloaded app in the App Store. ChatGPT VS DeepSeek: Will DeepSeek Dethrone ChatGPT? Continue watching to find out. #deepseek #chatgpt #openai #AI #artificialintelligence #nvidia #future #intelligence #technology #tech
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0:00
in the high stakes theater of artificial
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intelligence where trillion doll
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valuations hinge on silicon and
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algorithms a seismic trimmer just rocked
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Wall Street Nvidia the Titan of the AI
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Gold Rush plummeted 177% in a single day
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vaporizing nearly $600 billion in value
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the culprit a little known Chinese
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startup deep seek whose audacious claim
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to have built a cuttingedge AI model for
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just $5.6 million sent shock waves
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through an industry built on exorbitant
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GPU budgets and propri AR secrecy
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investors scrambled as broadcom and
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astrolabs nose-dived alongside Nvidia
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their losses painting a grim portrait of
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panic but beneath the chaos lies a
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deeper story a clash of philosophies
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shaking the very foundations of ai's
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future while giants like open Ai and
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Google bet billions on closed ecosystems
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and ever larger models deep seeks open
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source slight of hand using less
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powerful chips dodging us export curbs
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and slashing costs has exposed a
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vulnerability in the AI arms race is
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this the moment the market wakes up to
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the myth that bigger is better in recent
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years the rise of deep seek has sparked
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conversations about its impact on
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established giants like chat GPT with
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claims that it's diverting attention
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reshaping Market expectations and even
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crashing the AI ecosystem as we know it
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to understand this shift one must look
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at the interplay of factors like cost
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accuracy technological foundations and
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the subtle nuances of how these tools
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are designed to serve users the story of
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deep seeks Ascent isn't just about
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technical superiority it's a narrative
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of timing accessibility and the
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Relentless pursuit of solving problems
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that users didn't realize they had until
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a new Option appeared chat GPT launched
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by open AI in late 2022 quickly became a
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household name celebrated for its
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ability to generate human-like text
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answer complex questions and even mimic
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creative writing styles its underlying
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architecture GPT 3.5 and later GPT 4
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relied on vast computational resources
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and a training data set encompassing a
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significant portion of the internet for
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many it was the first time interacting
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with an AI that felt genuinely
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responsive almost conversational but
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this capability came at a cost both
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literal and figurative running such
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massive models required expensive GPU
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clusters and those costs trickled down
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to users through premium subscription
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tiers and API pricing that made
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large-scale integration prohibitive for
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smaller businesses or individual
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developers chat gpt's accuracy while
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impressive occasionally stumbled over
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Niche topics or real-time information
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given its knowledge cut off and the
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inherent challenges of filtering out
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biases or misinformation from its
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training data enter deep seek a relative
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newcomer that entered the scene with a
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different philosophy rather than chasing
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sheer scale deep seek focused on
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optimizing efficiency its models were
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designed to deliver comparable or in
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some cases Superior performance with
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fewer parameters reducing the
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computational footprint this efficiency
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translated to lower operational costs
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which deep- seek passed on to users
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through more affordable access tiers for
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developers and Enterprises this was a
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GameChanger suddenly integrating AI into
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applications didn't require navigating
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complex pricing grids or worrying about
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exponential costs as usage scaled deep
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seeks approach to GPU utilization also
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Drew attention by refining model
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architectures and leveraging Hardware
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specific optimizations it achieved
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faster inference times without relying
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on the most expensive cuttingedge gpus
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this made it accessible to a broader
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audience including those in regions with
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limited access to high-end
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infrastructure accuracy became another
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Battleground while chat GPT excelled in
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Broad general purpose interactions deep
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sea carved a niche by offering
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specialized models tailored to specific
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Industries legal medical technical
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support and fine-tuned on curated data
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sets this specialization reduced the
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hallucination problem that plagued
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earlier AI systems where models would
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generate plausible sounding but
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factually incorrect responses users
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began to notice that deep seeks outputs
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felt more precise in contexts requiring
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domain expertise even if its creativity
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and open-ended conversations lagged
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slightly behind chat gpt's flare the
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trade-off between breadth and depth
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became a defining factor in user
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preference those needing reliable
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factual accuracy and professional
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settings gravitated toward deep seek
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while creators and Casual users often
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stuck with chat GPT for its versatility
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and imaginative outputs the timing of
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deep seeks in entry into the market also
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played a crucial role by the time it
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launched the initial hype around
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generative AI had settled and users were
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becoming more Discerning the novelty of
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chatting with an AI had worn off
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replaced by demands for practicality and
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Roi deep seek positioned itself as a
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solution First Tool emphasizing
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Integrations developer friendly apis and
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transparent pricing chat GPT meanwhile
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faced criticism for its opaque updates
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and occasional struggles to keep Pace
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with user expectations such as delays in
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rolling out multimodal capabilities or
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addressing latency issues deep seeks
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agility in iterating its models and
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incorporating feedback gave it an edge
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in a market increasingly intolerant of
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stagnation image generation added
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another layer to this competition while
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chat GPT initially relied on
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Partnerships with tools like dolly for
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visual content deep seek introduced its
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own AI image generation framework deep
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seeks image model allowed users to tweak
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outputs at a granular level adjusting
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lighting texture or compositional
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balance through natural language prompts
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rather than relying on the trial and
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error approach common in earlier systems
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artists and marketers praise this
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functionality though some critics argued
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it over complicated the user experience
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for casual creators chat gpt's image
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offerings by contrast remained more
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userfriendly but less customizable
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appealing to those who prioritize speed
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and simplicity over fine grain control
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underlying these differences were
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philosophical divergences in how each
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platform approached AI development chat
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GP 's Journey reflected a commitment to
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pushing the boundaries of what large
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language models could achieve even if it
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meant prioritizing scale over
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specificity deep seek meanwhile embraced
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a less is more ethos arguing that's
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smarter model design and targeted
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training could achieve similar results
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with fewer resources this dichotomy
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mirrored broader debates in the AI
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Community about sustainability and
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scalability as concerns grew about the
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environmental impact of training massive
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models a single GPT for training run
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reportedly cons consumed energy
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equivalent to thousands of households
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deep seeks efficiency Centric narrative
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resonated with environmentally conscious
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users and organizations yet for all its
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advantages deep seek face challenges in
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dethroning chat GPT entirely brand
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recognition remained a formidable
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barrier chat GPT had become synonymous
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with AI in the public Consciousness much
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like Google did with search engines
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educational resources thirdparty
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tutorials and community support for chat
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GPT were vast creating a network effect
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that deep- seek struggled to replicate
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overnight moreover chat gpt's parent
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company open AI continued to innovate
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gradually addressing pain points around
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cost and accuracy while expanding its
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ecosystem through plugins and
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Partnerships the competition between the
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two platforms began to resemble a
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marathon rather than a Sprint with each
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leap frogging the other in specific
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areas while conceding ground elsewhere
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the question of who wins in this rivalry
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may miss the point what deep seeks rise
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under scores is a maturation of the AI
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Market a shift from monolithic one size
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fits all solutions to a diversified
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landscape where different tools cater to
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different needs for some chat gpt's
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creativity and brand power will always
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hold sway for others deep seeks
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affordability precision and nimbleness
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offer a compelling alternative what's
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clear is that the arrival of deep seek
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has forced a re-evaluation of what users
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expect from AI no longer just
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technological marveles but reliable
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cost-effective Partners in solving real
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world problems whether this disruption
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truly crashes the market or simply
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elevates it to new heights depends on
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how both platforms and their successors
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adapt to the everchanging demands of a
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world increasingly shaped by artificial
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intelligence if you like more daily
8:12
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8:14
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8:16
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