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Hey everybody, welcome back to 
the Elon Musk Podcast. 

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This is a show where we discuss 
the critical Crossroads, the 

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Shape, SpaceX, Tesla X, The 
Boring Company, and Neuralink. 

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I'm your host, Will Walden. 
In today's episode, we're going 

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to be talking about Google's new
ChatGPT competitor Gemini, also 

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a competitor to Elon Musk's X 
dot AI. 

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Google recently announced the 
launch of Gemini, its latest and

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most sophisticated artificial 
intelligence model, marking a 

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huge step in the company's 
efforts to compete in the 

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rapidly expanding field of 
generative AI. 

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Gemini, described as Google's 
largest and most capable AI 

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model, represents a new phase in
AI development with the 

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potential to enhance a wide 
array of Google's consumer apps 

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and devices, including the 
Google Pixel 8 Chrome. 

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Now this announcement is seen as
Google's response to the 

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unexpected success of Open AI's 
ChatGPT, and indicates a shift 

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in the company's strategic 
direction towards more advanced 

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AI integration across its 
products. 

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Now Gemini stands out from its 
multimodal competitors. 

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Gemini stands out for its 
multimodal capabilities, which 

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means it's it can process and 
generate responses from various 

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types of media inputs, including
text, images, audio, video, and 

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also programming code. 
This sets it apart from existing

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AI models, which typically focus
on a single type of input. 

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Sundar, the Google CEO, 
emphasized the significance of 

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this development in a blog post,
stating that this represents one

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of the most substantial science 
and engineering efforts 

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undertaken by the company to 
date. 

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Google's proprietary AI chatbot,
Bard has been upgraded with a 

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Gemini model and there are plans
to integrate Gemini into widely 

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used products like Google's 
search engine in the Chrome web 

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browser. 
Gemini's launch also highlights 

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Google's advancements in cloud 
computing as the model was 

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trained using a new generation 
of cloud based processors. 

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Now potentially this will boost 
the EI industry by making AI 

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training more accessible than it
is today. 

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The Gemini model comes in three 
different versions, Nano, 

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optimized for mobile devices and
app developers, Pro, designed 

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for a broad range of tasks and 
consumers, and Ultra, the most 

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advanced version currently 
undergoing safety testing and 

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Gemini. 
Ultra is being released 

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gradually to select customers 
and partners for early feedback.

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It is undergoing third party 
safety evaluations, part of 

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Google's commitment to 
responsible AI development. 

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And Google claims that in 
testing Gemini outperformed 

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other AI models and more than 
two dozen benchmarks commonly 

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used in AI research, 
particularly in tasks involving 

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reading comprehension, 
mathematical ability and multi 

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step reasoning. 
The company also highlights 

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Gemini's efficiency as it was 
trained on Google's own Tensor 

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Processing Units, or TP US, 
making it faster and cheaper to 

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run than previous models. 
And while Gemini's launches a 

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significant development in 
Google's AI strategy, there's 

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still concerns regarding the 
models potential to produce 

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misleading results, a known 
issue with large language 

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models. 
And Google has worked to improve

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the factuality of Gemini's 
responses, but acknowledges that

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these models can still produce 
incorrect information with high 

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confidence. 
To address this, additional 

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techniques are being used to 
improve the accuracy of 

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responses in products like Bard.
And the roll out of Gemini 

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represents Google's larger 
vision for AI where a single 

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underlying technology can be 
improved and then integrated 

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across a range of products, 
enhancing user experiences in 

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diverse ways. 
The models integration into 

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Google Search engine, add 
products and Chrome browser is 

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anticipated to significantly 
influence the company's future 

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direction and capabilities, and 
Gemini's launch also signifies 

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Google's ambition to reclaim its
position as a leader in AI 

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innovation. 
Particularly after being 

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perceived as caught off guard by
the rapid success of Open AI's 

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ChatGPT, Google's approach to AI
development remains cautious yet

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optimistic with a focus on 
ensuring the safety and 

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responsibility of its AI 
systems. 

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Amidst the landscape of 
competitive AI development, 

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Google's strategic positioning 
of Gemini is a deep commitment 

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to enhancing user interaction 
across its vast network of 

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services. 
And the multimodal nature of 

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Gemini enables a more intuitive 
and versatile user experience by

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integrating various forms of 
media input. 

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Gemini is positioning to 
revolutionize how users interact

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with their technology that 
they're used to now like 

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google.com, their phones and 
also their assistants the 

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bridging the gaps between 
different forms of digital 

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communication. 
This is particularly significant

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for mobile and web applications 
though, where seamless 

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integration of various media 
types can greatly enhance 

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functionality and user 
engagement. 

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And the introduction of Gemini 
suggests A strategic pivot for 

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Google in the realm of AI and 
also in the terms of search, 

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signifying a shift from more 
traditional singular focus on 

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web-based services to a more 
integrated approach. 

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This shift is expected to have 
significant implications for the

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future of Google's product 
development and user experience 

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strategies. 
And by leveraging Gemini's 

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advanced capabilities, Google is
poised to offer more 

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personalized, context aware 
services across all of its 

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platforms, potentially 
transforming the way you use 

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your search, interact, and 
consume digital content now. 

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Furthermore, Gemini's 
development aligns with Google's

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broader vision of harnessing AI 
from more efficient in 

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intelligent computing. 
The use of Google's Advanced 

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Tensor Processing units in 
training Gemini underscores the 

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company's emphasis on not only 
advancing AI capabilities, but 

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also on optimizing the 
efficiency and speed of AI 

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processes. 
This focus on efficiency as 

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crucial as it addresses one of 
the key challenges in the AI 

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field, the high computational 
cost of training and running 

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sophisticated models. 
And by improving efficiency, 

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Google not only enhances its own
AI capabilities, but also 

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contributes to the AI ecosystem 
by setting new standards and 

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computational efficiency and 
sustainability. 

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And the release of Gemini, 
therefore, is not just about 

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competing with other AI models 
like Open AIS ChatGPT, and GBT 

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4, but it's also Google's 
testament to advancing AI 

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technology in a more responsible
and efficient manner than other 

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companies. 
And they could potentially 

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reshape the landscape of AI 
applications and could be a 

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brand new era for Google in its 
pursuit of cutting edge AI 

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solutions. 
Thank you so much for tuning 

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into the show today. 
I really do appreciate your 

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support. 
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It helps out the show 

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and each other and I'll see you 
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