Welcome to Discover Daily by Perplexity , an AI-generated show on tech , science and culture . I'm Alex . Today we're exploring how birds and mammals have independently evolved complex brains , challenging our understanding of cognitive evolution . But first let's look at what else is happening across the world of technology and AI .
Our first story today , the Internal Revenue Service is set to acquire an NVIDIA SuperPod AI supercomputer . This powerful system combines 31 servers with advanced Blackwell processors , each containing eight processing units . It's designed to enhance the IRS's machine learning capabilities for tasks such as fraud detection and taxpayer behavior analysis .
The SuperPod will be installed at the IRS Computing Center in Martinsburg , west Virginia . While the exact cost isn't public yet , these systems typically start at $7 million . The acquisition is part of a broader AI transformation within the agency , which currently has 68 different AI-related projects in development .
While this system may be smaller than the massive AI training centers used by tech giants like OpenAI and Meta , it represents a significant computing resource for a government agency . This acquisition marks a notable technological advancement for the IRS .
The Research , applied Analytics and Statistics Division will operate the SuperPOD as part of their Compliance Data Warehouse project . The system will come with a substantial memory upgrade from NVIDIA enabling more sophisticated data analysis . Previous machine learning applications by this division have already shown promise in automated fraud detection and identity theft prevention .
While the hardware hasn't been purchased or installed yet , the SuperPOD's advanced AI capabilities are expected to enhance the agency's ability to identify complex patterns indicative of fraudulent activities . This technology investment reflects a growing trend of AI adoption in government operations , particularly in areas requiring sophisticated pattern recognition and data analysis .
Moving on to our second story , a new study has revealed that ChatGPT's energy consumption is much lower than previously estimated . The non-profit research institute EPIC-AI found that ChatGPT's latest model , gpt-4-0 , consumes approximately 0.3 watt-hours per query ten times less than earlier estimates .
But it's worth noting that these figures are approximations , as OpenAI hasn't publicly disclosed detailed energy consumption data . This significant reduction in energy use can be attributed to advancements in AI technology and more accurate calculation methods .
While some have compared ChatGPT's energy use to other digital services , it's important to understand that different measurement methodologies make direct comparisons challenging . To put this into perspective , typical household activities consume significantly more energy , with many common appliances using hundreds of watt-hours per hour of operation .
These comparisons help illustrate the scale , though exact figures can vary based on specific devices and usage patterns . Several factors contribute to this improved energy efficiency , including the implementation of more advanced hardware like NVIDIA H100 chips , optimization of AI systems and updated calculation methods that better reflect current technology .
These measurements specifically refer to standard text-based queries and don't include energy-intensive features like image generation or processing extremely long conversations , but the cumulative effect of millions of daily queries still results in substantial energy consumption .
The AI industry is investing in energy-efficient hardware and renewable energy sources to mitigate environmental impacts . As models become more sophisticated and handle more complex tasks , their energy requirements may increase , making these efficiency improvements even more crucial . Now let's dive into our main story of the day .
Recent research has revealed that birds and mammals have independently evolved complex brains through distinct developmental , structural and genetic pathways .
This showcases convergent evolution , achieving similar cognitive abilities despite profound differences in brain architecture and molecular mechanisms , and the University of the Basque Country used advanced techniques in spatial transcriptomics and mathematical modelling to uncover fundamental differences in brain development between birds and mammals .
Published in Science , this research actually comprised two complementary studies that together paint a fascinating picture of brain evolution . One key finding is that the pallium , a critical brain region responsible for cognitive functions , develops differently across species , despite sharing similar functional outcomes .
In birds and mammals , while the circuits perform comparable tasks , the neurons form during embryonic development at distinct locations and times . This divergence extends to the genetic tools employed for establishing cellular identity , resulting in unique cell types across species .
What's particularly interesting is that inhibitory neurons have remained remarkably similar across species for hundreds of millions of years , while excitatory neurons , responsible for information transmission , have evolved along dramatically different pathways .
In fact , only a small number of excitatory neurons in birds share genetic similarities with their mammalian counterparts , specifically in brain regions called the clostrum and hippocampus . The evolutionary paths of birds and mammals diverged millions of years ago , resulting in distinct sets of genes being used for sensory processing neurons in birds and mammals .
Yet nature has shown us that there isn't just one blueprint for building an intelligent brain . Despite these differences , both birds and mammals have achieved remarkably similar cognitive abilities through convergent evolution .
Many bird species demonstrate impressive problem-solving abilities and complex social behaviors , showing us that advanced cognition can emerge from very different neural architectures . The study challenges the traditional understanding of brain evolution , demonstrating that complex neural circuits can arise through diverse developmental pathways .
It provides crucial insights into the genetic and cellular mechanisms underlying the independent evolution of complex brains . That's it for today . Thanks for tuning in .
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In other Perplexity news , the company just launched Deep Research , a powerful new feature that digs deep into hundreds of sources to create thorough research reports . The tool , which is free to try and unlimited for pro users , can tackle complex research questions in just minutes .
Early tests show it's remarkably accurate , making it a promising tool for anyone needing in-depth research assistance . We'll be back with more stories that matter . Until then , stay curious .