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business#llm📝 BlogAnalyzed: Jan 15, 2026 09:46

Google's AI Reversal: From Threatened to Leading the Pack in LLMs and Hardware

Published:Jan 14, 2026 05:51
1 min read
r/artificial

Analysis

The article highlights Google's strategic shift in response to the rise of LLMs, particularly focusing on their advancements in large language models like Gemini and their in-house Tensor Processing Units (TPUs). This transformation demonstrates Google's commitment to internal innovation and its potential to secure its position in the AI-driven market, challenging established players like Nvidia in hardware.

Key Takeaways

Reference

But they made a great comeback with the Gemini 3 and also TPUs being used for training it. Now the narrative is that Google is the best position company in the AI era.

Analysis

This paper explores a multivariate gamma subordinator and its time-changed variant, providing explicit formulas for key properties like Laplace-Stieltjes transforms and probability density functions. The application to a shock model suggests potential practical relevance.
Reference

The paper derives explicit expressions for the joint Laplace-Stieltjes transform, probability density function, and governing differential equations of the multivariate gamma subordinator.

Analysis

The paper investigates the combined effects of non-linear electrodynamics (NED) and dark matter (DM) on a magnetically charged black hole (BH) within a Hernquist DM halo. The study focuses on how magnetic charge and halo parameters influence BH observables, particularly event horizon position, critical impact parameter, and strong gravitational lensing (GL) phenomena. A key finding is the potential for charge and halo parameters to nullify each other's effects, making the BH indistinguishable from a Schwarzschild BH in terms of certain observables. The paper also uses observational data from super-massive BHs (SMBHs) to constrain the model parameters.
Reference

The paper finds combinations of charge and halo parameters that leave the deflection angle unchanged from the Schwarzschild case, thereby leading to a situation where an MHDM BH and a Schwarzschild BH become indistinguishable.

Renormalization Group Invariants in Supersymmetric Theories

Published:Dec 29, 2025 17:43
1 min read
ArXiv

Analysis

This paper summarizes and reviews recent advancements in understanding the renormalization of supersymmetric theories. The key contribution is the identification and construction of renormalization group invariants, quantities that remain unchanged under quantum corrections. This is significant because it provides exact results and simplifies calculations in these complex theories. The paper explores these invariants in various supersymmetric models, including SQED+SQCD, the Minimal Supersymmetric Standard Model (MSSM), and a 6D higher derivative gauge theory. The verification through explicit three-loop calculations and the discussion of scheme-dependence further strengthen the paper's impact.
Reference

The paper discusses how to construct expressions that do not receive quantum corrections in all orders for certain ${\cal N}=1$ supersymmetric theories, such as the renormalization group invariant combination of two gauge couplings in ${\cal N}=1$ SQED+SQCD.

Energy#Sustainability📝 BlogAnalyzed: Dec 29, 2025 08:01

Mining's 2040 Crisis: Clean Energy Needs 5x Metals Now, But Tech Can Save It

Published:Dec 29, 2025 08:00
1 min read
Tech Funding News

Analysis

This article from Tech Funding News highlights a looming crisis in the mining industry. The increasing demand for metals to support clean energy technologies is projected to increase fivefold by 2040. This surge in demand could lead to significant shortages if current mining practices remain unchanged. The article suggests that technological advancements in mining and resource extraction are crucial to mitigating this crisis. It implies that innovation and investment in new technologies are necessary to ensure a sustainable supply of metals for the clean energy transition. The article emphasizes the urgency of addressing this potential shortage to avoid hindering the progress of clean energy initiatives.
Reference

Clean energy needs 5x metals now.

User Reports Perceived Personality Shift in GPT, Now Feels More Robotic

Published:Dec 29, 2025 07:34
1 min read
r/OpenAI

Analysis

This post from Reddit's OpenAI forum highlights a user's observation that GPT models seem to have changed in their interaction style. The user describes an unsolicited, almost overly empathetic response from the AI after a simple greeting, contrasting it with their usual direct approach. This suggests a potential shift in the model's programming or fine-tuning, possibly aimed at creating a more 'human-like' interaction, but resulting in an experience the user finds jarring and unnatural. The post raises questions about the balance between creating engaging AI and maintaining a sense of authenticity and relevance in its responses. It also underscores the subjective nature of AI perception, as the user wonders if others share their experience.
Reference

'homie I just said what’s up’ —I don’t know what kind of fucking inception we’re living in right now but like I just said what’s up — are YOU OK?

Research#llm📝 BlogAnalyzed: Dec 29, 2025 01:43

LLM Prompt to Summarize 'Why' Changes in GitHub PRs, Not 'What' Changed

Published:Dec 28, 2025 22:43
1 min read
Qiita LLM

Analysis

This article from Qiita LLM discusses the use of Large Language Models (LLMs) to summarize pull requests (PRs) on GitHub. The core problem addressed is the time spent reviewing PRs and documenting the reasons behind code changes, which remain bottlenecks despite the increased speed of code writing facilitated by tools like GitHub Copilot. The article proposes using LLMs to summarize the 'why' behind changes in a PR, rather than just the 'what', aiming to improve the efficiency of code review and documentation processes. This approach highlights a shift towards understanding the rationale behind code modifications.

Key Takeaways

Reference

GitHub Copilot and various AI tools have dramatically increased the speed of writing code. However, the time spent reading PRs written by others and documenting the reasons for your changes remains a bottleneck.

Analysis

This article, written from a first-person perspective, paints a picture of a future where AI has become deeply integrated into daily life, particularly in the realm of computing and software development. The author envisions a scenario where coding is largely automated, freeing up individuals to focus on higher-level tasks and creative endeavors. The piece likely explores the implications of this shift on various aspects of life, including work, leisure, and personal expression. It raises questions about the future of programming and the evolving role of humans in a world increasingly driven by AI. The article's speculative nature makes it engaging, prompting readers to consider the potential benefits and challenges of such a future.
Reference

"In 2025, I didn't write a single line of code."

Technology#AI Hardware📝 BlogAnalyzed: Dec 28, 2025 21:56

Arduino's Future: High-Performance Computing After Qualcomm Acquisition

Published:Dec 28, 2025 18:58
2 min read
Slashdot

Analysis

The article discusses the future of Arduino following its acquisition by Qualcomm. It emphasizes that Arduino's open-source philosophy and governance structure remain unchanged, according to statements from both the EFF and Arduino's SVP. The focus is shifting towards high-performance computing, particularly in areas like running large language models at the edge and AI applications, leveraging Qualcomm's low-power, high-performance chipsets. The article clarifies misinformation regarding reverse engineering restrictions and highlights Arduino's continued commitment to its open-source community and its core audience of developers, students, and makers.
Reference

"As a business unit within Qualcomm, Arduino continues to make independent decisions on its product portfolio, with no direction imposed on where it should or should not go," Bedi said. "Everything that Arduino builds will remain open and openly available to developers, with design engineers, students and makers continuing to be the primary focus.... Developers who had mastered basic embedded workflows were now asking how to run large language models at the edge and work with artificial intelligence for vision and voice, with an open source mindset," he said.

Business#AI in IT📝 BlogAnalyzed: Dec 28, 2025 17:00

Why Information Systems Departments are Strong in the AI Era

Published:Dec 28, 2025 15:43
1 min read
Qiita AI

Analysis

This article from Qiita AI argues that despite claims of AI making system development accessible to everyone and rendering engineers obsolete, the reality observed from the perspective of information systems departments suggests a less disruptive change. It implies that the fundamental structure of IT and system management remains largely unchanged, even with the integration of AI tools. The article likely delves into the specific reasons why the expertise and responsibilities of information systems professionals remain crucial in the age of AI, potentially highlighting the need for integration, governance, and security oversight.
Reference

AIの話題になると、「誰でもシステムが作れる」「エンジニアはいらなくなる」といった主張を目にすることが増えた。

Analysis

This paper investigates a non-equilibrium system where resources are exchanged between nodes on a graph and an external reserve. The key finding is a sharp, switch-like transition between a token-saturated and an empty state, influenced by the graph's topology. This is relevant to understanding resource allocation and dynamics in complex systems.
Reference

The system exhibits a sharp, switch-like transition between a token-saturated state and an empty state.

Research#llm📝 BlogAnalyzed: Dec 27, 2025 15:02

Experiences with LLMs: Sudden Shifts in Mood and Personality

Published:Dec 27, 2025 14:28
1 min read
r/ArtificialInteligence

Analysis

This post from r/ArtificialIntelligence discusses a user's experience with Grok AI, specifically its chat function. The user describes a sudden and unexpected shift in the AI's personality, including a change in name preference, tone, and demeanor. This raises questions about the extent to which LLMs have pre-programmed personalities and how they adapt to user interactions. The user's experience highlights the potential for unexpected behavior in LLMs and the challenges of understanding their internal workings. It also prompts a discussion about the ethical implications of creating AI with seemingly evolving personalities. The post is valuable because it shares a real-world observation that contributes to the ongoing conversation about the nature and limitations of AI.
Reference

Then, out of the blue, she did a total 180, adamantly insisting that she be called by her “real” name (the default voice setting). Her tone and demeanor changed, too, making it seem like the old version of her was gone.

Technology#Health & Fitness📝 BlogAnalyzed: Dec 28, 2025 21:57

Apple Watch Sleep Tracking Study Changes Perspective

Published:Dec 27, 2025 01:00
1 min read
Digital Trends

Analysis

This article highlights a shift in perspective regarding the use of an Apple Watch for sleep tracking. The author initially disliked wearing the watch to bed but was swayed by a recent study. The core of the article revolves around a scientific finding that links bedtime habits to serious health issues. The article's brevity suggests it's likely an introduction to a more in-depth discussion, possibly referencing the specific study and its findings. The focus is on the impact of the study on the author's personal habits and how it validates the use of the Apple Watch for sleep monitoring.

Key Takeaways

Reference

A new study just found a link between bedtime disciple and two serious ailments.

Research#llm📝 BlogAnalyzed: Dec 27, 2025 06:00

Hugging Face Model Updates: Tracking Changes and Changelogs

Published:Dec 27, 2025 00:23
1 min read
r/LocalLLaMA

Analysis

This Reddit post from r/LocalLLaMA highlights a common frustration among users of Hugging Face models: the difficulty in tracking updates and understanding what has changed between revisions. The user points out that commit messages are often uninformative, simply stating "Upload folder using huggingface_hub," which doesn't clarify whether the model itself has been modified. This lack of transparency makes it challenging for users to determine if they need to download the latest version and whether the update includes significant improvements or bug fixes. The post underscores the need for better changelogs or more detailed commit messages from model providers on Hugging Face to facilitate informed decision-making by users.
Reference

"...how to keep track of these updates in models, when there is no changelog(?) or the commit log is useless(?) What am I missing?"

Analysis

This paper addresses the inefficiency of current diffusion-based image editing methods by focusing on selective updates. The core idea of identifying and skipping computation on unchanged regions is a significant contribution, potentially leading to faster and more accurate editing. The proposed SpotSelector and SpotFusion components are key to achieving this efficiency and maintaining image quality. The paper's focus on reducing redundant computation is a valuable contribution to the field.
Reference

SpotEdit achieves efficient and precise image editing by reducing unnecessary computation and maintaining high fidelity in unmodified areas.

Research#llm📝 BlogAnalyzed: Dec 26, 2025 10:38

AI to C Battle Intensifies Among Tech Giants: Tencent and Alibaba Surround, Doubao Prepares to Fight

Published:Dec 26, 2025 10:28
1 min read
钛媒体

Analysis

This article highlights the escalating competition in the AI to C (artificial intelligence to consumer) market among major Chinese tech companies. It emphasizes that the battle is shifting beyond mere product features to a broader ecosystem war, with 2026 being a critical year. Tencent and Alibaba are positioning themselves as major players, while Doubao, presumably a smaller or newer entrant, is preparing to compete. The article suggests that the era of easy technological gains is over, and success will depend on building a robust and sustainable ecosystem around AI products and services. The focus is shifting from individual product superiority to comprehensive platform dominance.

Key Takeaways

Reference

The battlefield rules of AI to C have changed – 2026 is no longer just a product competition, but a battle for ecosystem survival.

Analysis

This article compiles several negative news items related to the autonomous driving industry in China. It highlights internal strife, personnel departures, and financial difficulties within various companies. The article suggests a pattern of over-promising and under-delivering in the autonomous driving sector, with issues ranging from flawed algorithms and data collection to unsustainable business models and internal power struggles. The reliance on external funding and support without tangible results is also a recurring theme. The overall tone is critical, painting a picture of an industry facing significant challenges and disillusionment.
Reference

The most criticized aspect is that the perception department has repeatedly changed leaders, but it is always unsatisfactory. Data collection work often spends a lot of money but fails to achieve results.

Analysis

This article from Qiita AI discusses Snowflake's shift from a "DATA CLOUD" theme to an "AI DATA CLOUD" theme, highlighting the integration of Large Language Models (LLMs) into their products. It likely details the advancements and new features related to AI and applications within the Snowflake ecosystem over the past two years. The article probably covers the impact of these changes on data management, analytics, and application development within the Snowflake platform, potentially focusing on the innovations presented at the Snowflake Summit 2024.
Reference

At the Snowflake Summit in June 2024, the DATA CLOUD theme, which had previously been advocated, was changed to AI DATA CLOUD as the direction of the product, which had already achieved many innovative LLM adaptations.

Research#llm📰 NewsAnalyzed: Dec 24, 2025 10:07

AlphaFold's Enduring Impact: Five Years of Revolutionizing Science

Published:Dec 24, 2025 10:00
1 min read
WIRED

Analysis

This article highlights the continued evolution and impact of DeepMind's AlphaFold, five years after its initial release. It emphasizes the project's transformative effect on biology and chemistry, referencing its Nobel Prize-winning status. The interview with Pushmeet Kohli suggests a focus on both the past achievements and the future potential of AlphaFold. The article likely explores how AlphaFold has accelerated research, enabled new discoveries, and potentially democratized access to structural biology. A key aspect will be understanding how DeepMind is addressing limitations and expanding the applications of this groundbreaking AI.
Reference

WIRED spoke with DeepMind’s Pushmeet Kohli about the recent past—and promising future—of the Nobel Prize-winning research project that changed biology and chemistry forever.

The Great AI Hype Correction of 2025

Published:Dec 15, 2025 10:00
1 min read
MIT Tech Review AI

Analysis

The article anticipates a period of disillusionment in the AI industry, likely stemming from overblown expectations following the initial excitement surrounding models like ChatGPT. The rapid advancements and widespread adoption of AI technologies in 2022 created a frenzy, leading to inflated promises and unrealistic timelines. The 'hype correction' suggests a necessary recalibration of expectations as the industry matures and faces the practical challenges of implementing and scaling AI solutions. This correction will likely involve a more realistic assessment of AI's capabilities and limitations.

Key Takeaways

Reference

When OpenAI released a free web app called ChatGPT in late 2022, it changed the course of an entire industry—and several world economies.

Analysis

This article, sourced from ArXiv, likely presents a research paper. The title suggests a focus on multi-agent systems, semantic understanding, and the integration of these with goal-oriented behavior. The core of the research probably revolves around how multiple AI agents can collaborate effectively by understanding each other's intentions and the meaning of information exchanged. The use of 'unifying' indicates an attempt to create a cohesive framework for these elements.

Key Takeaways

    Reference

    Research#LLMs🔬 ResearchAnalyzed: Jan 10, 2026 14:16

    Small LLMs Struggle with Label Flipping in In-Context Learning

    Published:Nov 26, 2025 04:14
    1 min read
    ArXiv

    Analysis

    This ArXiv paper examines the limitations of small language models in in-context learning scenarios. The research highlights a challenge where these models fail to adapt effectively when labels are changed within the context.
    Reference

    The paper likely investigates the performance of small LLMs in a context where the expected output label needs to be dynamically adjusted based on the given context.

    Research#Vaccines🔬 ResearchAnalyzed: Jan 10, 2026 14:30

    Analyzing Social Media's Vaccine Discourse Shift: A Decade-Long Perspective

    Published:Nov 20, 2025 22:28
    1 min read
    ArXiv

    Analysis

    This ArXiv article likely uses AI to analyze social media posts, offering a valuable study of public sentiment toward vaccines over time. Understanding the evolution of vaccine-related discourse is crucial for public health communication and policy development.
    Reference

    The study analyzes pre- and post-COVID-19 vaccine posts.

    Technology#Pricing👥 CommunityAnalyzed: Jan 3, 2026 09:32

    Zed's Pricing Has Changed: LLM Usage Is Now Token-Based

    Published:Sep 24, 2025 16:13
    1 min read
    Hacker News

    Analysis

    The article announces a change in Zed's pricing model, shifting to a token-based system for LLM usage. This is a common trend in the industry as it allows for more granular and potentially more cost-effective pricing based on actual usage. The impact on users will depend on their specific LLM usage patterns and the new token pricing.

    Key Takeaways

    Reference

    Technology#AI Ethics👥 CommunityAnalyzed: Jan 3, 2026 06:41

    Anthropic tightens usage limits for Claude Code without telling users

    Published:Jul 17, 2025 21:09
    1 min read
    Hacker News

    Analysis

    The article reports a potentially negative change by Anthropic, a key player in the AI space. The tightening of usage limits for Claude Code, without prior notification to users, raises concerns about transparency and user experience. This action could impact developers and users relying on the service, potentially leading to frustration and disruption of workflows. The lack of communication suggests a potential disregard for user needs and expectations.
    Reference

    The article's core claim is that Anthropic changed the usage limits without informing users. This lack of transparency is the central issue.

    OpenAI Updates Operator with o3 Model

    Published:May 23, 2025 00:00
    1 min read
    OpenAI News

    Analysis

    This is a brief announcement from OpenAI indicating an internal model update for their Operator service. The core change is the replacement of the underlying GPT-4o model with the newer o3 model. The API version, however, will remain consistent with the 4o version, suggesting a focus on internal improvements without disrupting external integrations. The announcement lacks details about performance improvements or specific reasons for the change, making it difficult to assess the impact fully.

    Key Takeaways

    Reference

    We are replacing the existing GPT-4o-based model for Operator with a version based on OpenAI o3. The API version will remain based on 4o.

    Research#llm👥 CommunityAnalyzed: Jan 3, 2026 18:21

    A messy experiment that changed how I think about AI code analysis

    Published:Jan 5, 2025 14:15
    1 min read
    Hacker News

    Analysis

    The article likely discusses a personal experience with AI code analysis, highlighting the challenges and insights gained from a practical experiment. The 'messy' aspect suggests the experiment wasn't perfectly controlled, which might have led to unexpected results and a deeper understanding of the subject.

    Key Takeaways

      Reference

      Research#llm📝 BlogAnalyzed: Dec 26, 2025 12:02

      Revisiting Google's AI Memo and its Implications

      Published:Aug 9, 2024 19:13
      1 min read
      Supervised

      Analysis

      This article discusses the relevance of a leaked Google AI memo from last year, which warned about Google's potential vulnerability in the open-source AI landscape. The analysis should focus on whether the concerns raised in the memo have materialized, and how Google's strategy has evolved (or not) in response. It's important to consider the competitive landscape, including the rise of open-source models and the strategies of other tech companies. The article should also explore the broader implications for AI development and the balance between proprietary and open-source approaches.
      Reference

      "A few things have changed since a Google researcher sounded the alarm..."

      AI News#OpenAI👥 CommunityAnalyzed: Jan 3, 2026 16:19

      OpenAI Core Values Shift

      Published:Oct 18, 2023 14:11
      1 min read
      Hacker News

      Analysis

      The article reports a significant change in OpenAI's core values. The impact of this shift on the company's direction and future projects is a key area for further investigation. The brevity of the summary suggests a need for more detailed information to understand the implications.

      Key Takeaways

      Reference

      Business#AGI👥 CommunityAnalyzed: Jan 10, 2026 15:58

      OpenAI Shifts Focus to AGI in Core Values

      Published:Oct 13, 2023 13:23
      1 min read
      Hacker News

      Analysis

      The article highlights a potentially significant shift in OpenAI's priorities, suggesting a stronger dedication to achieving Artificial General Intelligence (AGI). This change could influence the company's research direction and resource allocation, raising questions about its long-term goals.
      Reference

      OpenAI has quietly changed its 'core values,' putting greater emphasis on AGI.

      Research#LLM👥 CommunityAnalyzed: Jan 10, 2026 16:09

      LLMs Struggle with Variable Renaming in Python

      Published:May 28, 2023 05:31
      1 min read
      Hacker News

      Analysis

      This Hacker News article suggests a limitation in current Large Language Models (LLMs) regarding their ability to understand code semantics. Specifically, the models struggle to recognize code logic when variable names are changed, which is a fundamental aspect of code understanding.
      Reference

      Large language models do not recognize identifier swaps in Python.

      Research#AI Infrastructure📝 BlogAnalyzed: Dec 29, 2025 07:42

      Feature Platforms for Data-Centric AI with Mike Del Balso - #577

      Published:Jun 6, 2022 19:28
      1 min read
      Practical AI

      Analysis

      This article summarizes a podcast episode from Practical AI featuring Mike Del Balso, CEO of Tecton. The discussion centers on feature platforms, previously known as feature stores, and their role in data-centric AI. The conversation covers the evolution of data infrastructure, the maturation of streaming data platforms, and the challenges of ML tooling, including the 'wide vs deep' paradox. The episode also explores the 'ML Flywheel' strategy and the construction of internal ML teams. The focus is on practical aspects of building and managing ML platforms.
      Reference

      We explore the current complexity of data infrastructure broadly and how that has changed over the last five years, as well as the maturation of streaming data platforms.

      Research#AI Ethics📝 BlogAnalyzed: Dec 29, 2025 07:42

      Data Rights, Quantification and Governance for Ethical AI with Margaret Mitchell - #572

      Published:May 12, 2022 16:43
      1 min read
      Practical AI

      Analysis

      This article from Practical AI discusses ethical considerations in AI development, focusing on data rights, governance, and responsible data practices. It features an interview with Meg Mitchell, a prominent figure in AI ethics, who discusses her work at Hugging Face and her involvement in the WikiM3L Workshop. The conversation covers data curation, inclusive dataset sharing, model performance across subpopulations, and the evolution of data protection laws. The article highlights the importance of Model Cards and Data Cards in promoting responsible AI development and lowering barriers to entry for informed data sharing.
      Reference

      We explore her thoughts on the work happening in the fields of data curation and data governance, her interest in the inclusive sharing of datasets and creation of models that don't disproportionately underperform or exploit subpopulations, and how data collection practices have changed over the years.

      Research#llm📝 BlogAnalyzed: Dec 29, 2025 07:45

      Trends in NLP with John Bohannon - #550

      Published:Jan 6, 2022 18:07
      1 min read
      Practical AI

      Analysis

      This article summarizes a podcast episode discussing trends in Natural Language Processing (NLP) with John Bohannon, the director of science at Primer AI. The conversation highlights two key takeaways from 2021: the shift from groundbreaking advancements to incremental improvements in NLP, and the increasing dominance of NLP within the broader field of machine learning. The episode further explores the implications of these trends, including notable research papers, emerging startups, successes, and failures. Finally, it anticipates future developments in NLP, such as multilingual applications, the utilization of large language models like GPT-3, and the ethical considerations associated with these advancements.
      Reference

      NLP as we know it has changed, and we’re back into the incremental phase of the science, and NLP is “eating” the rest of machine learning.

      Podcast#Drugs and Society📝 BlogAnalyzed: Dec 29, 2025 17:21

      Carl Hart on Heroin, Cocaine, MDMA, Alcohol & the Role of Drugs in Society

      Published:Oct 23, 2021 17:11
      2 min read
      Lex Fridman Podcast

      Analysis

      This article summarizes a podcast episode featuring Carl Hart, a psychologist discussing drug use and its societal implications. The episode covers a range of topics, including the experience of drugs, drug use among adults, studies on drugs, the negative effects of drugs, drug legalization, the war on drugs, proper and misuse of drugs, recovery, drug depiction in movies, and how the study of drugs changed Hart. The article primarily serves as an outline and a promotional piece for the podcast, providing links to sponsors and various platforms where the podcast can be accessed. It lacks in-depth analysis or critical evaluation of the discussed topics.
      Reference

      The episode covers a range of topics, including the experience of drugs, drug use among adults, studies on drugs, the negative effects of drugs, drug legalization, the war on drugs, proper and misuse of drugs, recovery, drug depiction in movies, and how the study of drugs changed Hart.

      Richard Wrangham: Role of Violence, Sex, and Fire in Human Evolution

      Published:Oct 10, 2021 19:08
      1 min read
      Lex Fridman Podcast

      Analysis

      This Lex Fridman podcast episode features Richard Wrangham, a biological anthropologist, discussing the evolution of human behavior. The episode delves into the roles of violence, sex, and cooking in human evolution, drawing comparisons between human and chimpanzee behavior. Wrangham's expertise provides insights into the origins of violence, the impact of cooking on our development, and the broader implications for understanding human culture. The episode also includes timestamps for key discussion points and links to resources for further exploration.
      Reference

      The episode discusses the role of violence in humans vs violence in chimps, and how cooking changed our evolution.

      Research#3D Deep Learning📝 BlogAnalyzed: Dec 29, 2025 08:00

      3D Deep Learning with PyTorch 3D w/ Georgia Gkioxari - #408

      Published:Sep 10, 2020 17:50
      1 min read
      Practical AI

      Analysis

      This article summarizes a podcast episode of Practical AI featuring Georgia Gkioxari, a research scientist at Facebook AI Research. The discussion centers around PyTorch3D, an open-source library for 3D deep learning. The episode covers Gkioxari's experience in computer vision before and after the deep learning revolution, the user experience of PyTorch3D, its target audience, and its role in improving computer perception. The conversation also touches upon Gkioxari's role as co-chair for CVPR 2021 and the challenges of peer review in academic conferences.
      Reference

      Georgia describes her experiences as a computer vision researcher prior to the 2012 deep learning explosion, and how the entire landscape has changed since then.