Exploring the Reality of AI Adoption in Various Sectors: The AI Today podcast offers insights into the practical implementation of AI in various sectors, providing a balanced perspective and addressing budgets, resources, skill sets, and knowledge gaps.
The AI Today podcast, which has been running for four years with over 200 episodes, provides unique insights into the adoption and education of artificial intelligence (AI) in various sectors, including government at international, federal, state, and local levels. The hosts, Kathleen and Ron, have interviewed numerous thought leaders from both the public and private sectors to gain a balanced perspective on AI. They started the podcast as analysts, wanting to understand the reality behind the hype and what organizations are actually implementing in terms of AI technologies. The podcast offers valuable information on budgets, resources, skill sets, and knowledge gaps in the AI industry. By interviewing a diverse range of guests, the AI Today podcast provides a much-needed reality check in the ever-evolving world of AI.
Real-world challenges of AI implementation in government: Despite the hype, AI implementation in government faces challenges like data governance, security, ownership, and efficiency.
While there is a significant amount of hype surrounding AI and its progress, the reality of AI implementation in practice, particularly in government agencies, can be quite different. The Bureau of the Fiscal Service, which manages the inflows and outflows of government funds, is an example of an agency dealing with massive amounts of data, making AI and machine learning crucial for extracting value and addressing challenges such as fraud, efficiency, optimization, and automation. However, the implementation of AI in government faces challenges including data governance, data security, data ownership, and related areas. These issues are especially relevant in the current discussion around data ownership. Overall, the podcast aims to provide informed perspectives on AI and dispel hype by discussing real-world applications and challenges.
Implementing AI projects: Follow a well-defined methodology: Define the problem, identify data needs, prepare the data, build the model, evaluate it, and operationalize it using a methodology like CRISP-DM to ensure project success
When implementing AI projects, whether it's through vendors or in-house, it's crucial to have a well-defined methodology in place. This methodology should cover the entire pipeline, from defining the problem to operationalizing the model. A commonly used methodology is CRISP-DM (Cross Industry Standard Process for Data Mining), which has been in use since the late 1990s. This methodology emphasizes the importance of starting with the problem, identifying the required data, preparing the data, building the model, evaluating it, and finally operationalizing it. Neglecting the early stages of data preparation can lead to failed projects. It's essential to remember that without proper data preparation, all efforts in model building and evaluation will be in vain. Therefore, prioritizing a methodology and ensuring its implementation is vital for successful AI projects.
Addressing the high failure rate of AI projects with CPMAI: CPMAI, an iterative version of CRISP-DM, provides specific guidance for machine learning projects, focusing on data preparation, feature augmentation, and model operationalization, increasing chances of success in AI projects.
The failure rate of AI projects is high, estimated to be around 78%, often due to insufficient attention paid to data quality. To address this issue, an iterated version of the CRISP-DM methodology, called CPMAI, was developed. CPMAI provides more specific guidance for machine learning projects, focusing on data preparation, feature augmentation, and model operationalization, which are unique challenges in the AI context. By using a well-defined methodology like CPMAI, organizations can increase their chances of success in AI projects. The federal and state governments, which have been approaching AI initiatives in an ad hoc manner, could greatly benefit from implementing a structured methodology like CPMAI. Several government agencies, including the IRS, US Postal Service, and Department of Energy, have already begun using this methodology with positive results.
Government Emphasizes Proven Methodologies for AI Implementation: Federal and state governments are investing in AI, with the federal government pushing for methodology certification and documentation, while state and local governments rely on purchasing solutions due to resource limitations. The GSA acts as a 'center of excellence' to promote efficient spending and prevent unnecessary costs.
Both at the federal and state/local levels, governments are investing in artificial intelligence (AI) but are emphasizing the importance of vendors following proven methodologies for AI implementation. The federal government, with its larger budget, is pushing for methodology certification and documentation from vendors, while state and local governments often rely on purchasing AI solutions due to talent and resource limitations. The General Services Administration (GSA) serves as a "center of excellence" for the government, overseeing contracts and promoting efficient spending. They have a center specifically for AI, which aims to prevent unnecessary spending and ensure effective implementation. Overall, the emphasis is on ensuring transparency and accountability in AI adoption by government entities.
AI in Federal Government: Improving Data Efficiency and Accuracy: The GSA Center of Excellence is leading the way in implementing AI in the federal government, focusing on data-centric issues and removing humans from certain processes through technologies like NLP and RPA.
The use of AI, particularly in the federal government, is focused on data-centric issues, specifically data availability and quality. The GSA Center of Excellence is leading the way in establishing best practices for implementing AI, with a goal of removing humans from the loop in certain processes. While robotic process automation (RPA) is a common starting point, it's important to note that it's not true AI. Instead, true AI applications include natural language processing (NLP), which is being used in various federal agencies for tasks such as document analysis and chatbot communication. For example, USCIS has a chatbot named Emma that can communicate in Spanish and English, and the USPTO is using machine learning for patent search. The Bureau of Labor Statistics has even used NLP for injury classification, moving away from manual coding and survey-based data collection. Overall, the implementation of AI in the federal government is focused on improving efficiency and accuracy, particularly in areas where data processing is a significant challenge.
State governments face unique challenges in implementing AI and ML: California's CEO, Joy Bonaguro, is fostering collaboration and data sharing to address unique challenges in implementing AI and ML in state governments, while federal governments focus on cutting-edge research and exploration.
Artificial intelligence (AI) and machine learning (ML) are making significant impacts at both the federal and state levels of government. While the federal government may focus on cutting-edge research and exploration, such as using ML for analyzing satellite data or implementing conversational patterns for customer service, state governments face unique challenges. California, for instance, is a large and complex entity with a significant population and numerous systems. State governments are budget-constrained and have limited control over local jurisdictions, which often means crucial data is locked up at the county and city levels. However, California's CEO, Joy Bonaguro, is working to address this by fostering collaboration and data sharing between various entities. Despite the differences, both federal and state governments are harnessing the power of AI and ML to improve services, enhance decision-making, and address pressing issues.
Governments Prioritizing Self-Service, Automation, and Collaboration for Data Needs During COVID-19: Governments are adapting to budget constraints by prioritizing self-service, automation, and collaboration with small companies, students, and colleges to extract more value from their data during the COVID-19 pandemic.
The COVID-19 pandemic has significantly impacted the data systems and processes of both large and small governments. The focus has been on health information, unemployment, business shutdowns, and work from home environments. States, in particular, are facing budget constraints and need to prioritize their resources. As a result, there's a growing trend towards self-service, automation, and collaboration with small companies, students, and colleges to extract more value from their data. For instance, North Dakota, with its unique circumstances, is also making strides in this area. The CDO panel at the AI and Government community event provided valuable insights from the perspectives of Connecticut, Virginia, and Arkansas. Overall, governments at all levels are recognizing the importance of data in addressing the challenges of the pandemic and beyond.
The importance of effective data management and utilization in government: 23 states need to consider hiring and investing in a chief data officer for data-driven decision making, focusing on data rather than applications or systems demonstrates its power in public health and safety contexts.
Despite geographical and population differences among states, the need for effective data management and utilization is a common challenge and priority for all levels of government. While there may be unique obstacles, the efforts of chief data officers and other officials to address these issues and leverage technology demonstrate the importance of data in driving informed decision-making. With the increasing awareness and value placed on data, it's crucial for the remaining 23 states without chief data officers to consider hiring and investing in this role to keep up with the data-driven landscape. The focus on data rather than applications or systems is a testament to its power and potential to help make better decisions, especially in the context of public health and safety. Overall, the conversations with various government levels offer valuable insights into the ongoing efforts to harness the power of data and technology for the benefit of their constituents. For more in-depth discussions on this topic, listeners are encouraged to explore the interviews on the VA Today podcast.
Impact of AI on various industries and its transformative power: AI enhances customer service, revolutionizes healthcare, automates finance tasks, requires human-AI collaboration, and raises ethical concerns.
Kathleen and Ron shared valuable insights about the current state and future potential of AI in various industries during this episode of Scanit Today's Let's Talk AI Podcast. They discussed the impact of AI on customer service, healthcare, and finance industries, among others. Kathleen emphasized the importance of human-AI collaboration, while Ron highlighted the potential for AI to automate repetitive tasks and improve efficiency. They also touched upon the ethical considerations and challenges associated with AI implementation. Overall, the conversation underscored the transformative power of AI and its growing presence in our daily lives. To learn more about the topics discussed, listeners can check out the articles on Scanit Today's website and subscribe to their weekly newsletter. Don't forget to listen to all of their episodes and subscribe to both Scanit Today's and AI Today's podcasts. Remember to leave reviews and ratings to help more people discover these informative podcasts.
AI in the US State and Federal Governments with the hosts of the AI Today Podcast
Recent Episodes from Last Week in AI
# 182 - Alexa 2.0, MiniMax, Surskever raises $1B, SB 1047 approved
Our 182nd episode with a summary and discussion of last week's big AI news! With hosts Andrey Kurenkov and Jeremie Harris.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/. If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
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Sponsors:
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In this episode:
- OpenAI's move into hardware production and Amazon's strategic acquisition in AI robotics. - Advances in training language models with long-context capabilities and California's pending AI regulation bill. - Strategies for safeguarding open weight LLMs against adversarial attacks and China's rise in chip manufacturing. - Sam Altman's infrastructure investment plan and debates on AI-generated art by Ted Chiang.
Timestamps + Links:
- (00:00:00) Intro / Banter
- (00:05:15) Response to listener comments / corrections
- Tools & Apps
- Applications & Business
- (00:14:56) Ilya Sutskever’s startup, Safe Superintelligence, raises $1B
- (00:22:20) TSMC’s A16 Process Creates a Buzz Before Mass Production, as OpenAI Reportedly Secures Capacity
- (00:29:13) Amazon hires the founders of AI robotics startup Covariant
- (00:33:33) OpenAI weighs changes to corporate structure amid latest funding talks
- (00:37:43) Chinese GPU-maker XCT, once valued at $2.1B, is on the verge of collapse — shareholders now suing founder
- (00:40:34) TSMC aims to ready next-gen silicon photonics for AI in 5 years
- Projects & Open Source
- Research & Advancements
- (00:48:32) Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning
- (00:55:52) 100M Token Context Windows
- (01:03:50) Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling
- (01:06:16) AnyGraph : An Effective and Efficient Graph Foundation Model Designed to Address the Multifaceted Challenges of Structure and Feature Heterogeneity Across Diverse Graph Datasets
- Policy & Safety
- (01:08:16) California Legislature Approves Bill Proposing Sweeping A.I. Restrictions
- (01:11:14) Tamper-Resistant Safeguards for Open-Weight LLMs
- (01:17:12) China's chip capabilities just 3 years behind TSMC, teardown shows
- (01:20:50) China Threatens to Cut Off ASML Over New US Chip Curbs
- (01:23:22) Altman Infrastructure Plan Aims to Spend Tens of Billions in US
- Synthetic Media & Art
- (01:34:28) Outro
#181 - Google Chatbots, Cerebras vs Nvidia, AI Doom, ElevenLabs Controversy
Our 181st episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov and Jeremie Harris
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
In this episode:
- Google's AI advancements with Gemini 1.5 models and AI-generated avatars, along with Samsung's lithography progress. - Microsoft's Inflection usage caps for Pi, new AI inference services by Cerebrus Systems competing with Nvidia. - Biases in AI, prompt leak attacks, and transparency in models and distributed training optimizations, including the 'distro' optimizer. - AI regulation discussions including California’s SB1047, China's AI safety stance, and new export restrictions impacting Nvidia’s AI chips.
Timestamps + Links:
- (00:00:00) Intro / Banter
- (00:03:08)Response to listener comments / corrections
- Tools & Apps
- (00:09:19) Google’s custom AI chatbots have arrived
- (00:12:52) Google releases three new experimental AI models
- (00:17:14) Google Gemini will let you create AI-generated people again
- (00:22:32) Five months after Microsoft hired its founders, Inflection adds usage caps to Pi
- (00:26:42:) Plaud takes a crack at a simpler AI pin
- Applications & Business
- (00:30:31) Cerebras Systems throws down gauntlet to Nvidia with launch of ‘world’s fastest’ AI inference service
- (00:41:06) Nvidia announces $50 billion stock buyback
- (00:46:24) OpenAI in talks to raise funding that would value it at more than $100 billion
- (00:50:44) OpenAI Aims to Release New AI Model, ‘Strawberry,’ in Fall
- (00:52:53) 3 Co-Founders Leave French AI Startup H Amid ‘Operational Differences’
- (00:57:29) Samsung to Adopt High-NA Lithography Alongside Intel, Ahead of TSMC
- (01:02:11) Unitree's $16,000 G1 could become the first mainstream humanoid robot
- Projects & Open Source
- Research & Advancements
- Policy & Safety
- (01:47:12) U.S. AI Safety Institute Signs Agreements Regarding AI Safety Research, Testing and Evaluation With Anthropic and OpenAI
- (01:50:46) China’s Views on AI Safety Are Changing—Quickly
- (01:56:27) Poll: 7 in 10 Californians Support SB1047, Will Blame Governor Newsom for AI-Enabled Catastrophe if He Vetoes
- (02:01:31) Elon Musk voices support for California bill requiring safety tests on AI models
- (02:03:55) Chinese Engineers Reportedly Accessing NVIDIA’s High-End AI Chips Through Decentralized “GPU Rental Services”
- (02:08:25) U.S. gov't tightens China restrictions on supercomputer component sales
- Synthetic Media & Art
- (02:14:06) Outro
#180 - Ideogram v2, Imagen 3, AI in 2030, Agent Q, SB 1047
Our 180th episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
If you would like to get a sneak peek and help test Andrey's generative AI application, go to Astrocade.com to join the waitlist and the discord.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
Episode Highlights:
- Ideogram AI's new features, Google's Imagine 3, Dream Machine 1.5, and Runway's Gen3 Alpha Turbo model advancements.
- Perplexity's integration of Flux image generation models and code interpreter updates for enhanced search results.
- Exploration of the feasibility and investment needed for scaling advanced AI models like GPT-4 and Agent Q architecture enhancements.
- Analysis of California's AI regulation bill SB1047 and legal issues related to synthetic media, copyright, and online personhood credentials.
Timestamps + Links:
- (00:00:00) Intro / Banter
- (00:01:08) Response to Listener Comments / Corrections
- Tools & Apps
- (00:03:58) Ideogram AI expands its features with v2 model and color palette options
- (00:07:48) Google Releases Powerful AI Image Generator You Can Use for Free
- (00:11:41) Perplexity adds Flux.1 model for Pro users alongside Playground v3 update
- (00:13:58) Luma drops Dream Machine 1.5 — here’s what’s new
- (00:17:49) Runway’s Gen-3 Alpha Turbo is here and can make AI videos faster than you can type
- (00:20:21) Perplexity’s latest update improves code interpreter, charts included
- Applications & Business
- (00:24:14) AMD buying server maker ZT Systems for $4.9 billion as chipmakers strengthen AI capabilities
- (00:28:55) Ars Technica content is now available in OpenAI services
- (00:34:08) Anysphere, a GitHub Copilot rival, has raised $60M Series A at $400M valuation from a16z, Thrive, sources say
- 00:38:32 Stability AI appoints new Chief Technology Officer
- (00:41:45) Cruise’s robotaxis are coming to the Uber app in 2025
- Projects & Open Source
- (00:44:16) AI21 Introduces the Jamba Model Family: The most powerful and efficient long-context models for the enterprise
- (00:53:47) Microsoft reveals Phi-3.5 — this new small AI model outperforms Gemini and GPT-4o
- (00:57:33) Nvidia’s Llama-3.1-Minitron 4B is a small language model that punches above its weight
- (01:00:58) Open source Dracarys models ignite generative AI fired coding
- Research & Advancements
- Policy & Safety
- (01:38:20) California weakens bill to prevent AI disasters before final vote, taking advice from Anthropic
- (01:48:14) Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online
- (01:52:44) Showing SAE Latents Are Not Atomic Using Meta-SAEs
- Synthetic Media & Art
- (02:01:43) Outro
#179 - Grok 2, Gemini Live, Flux, FalconMamba, AI Scientist
Our 179th episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
If you would like to get a sneak peek and help test Andrey's generative AI application, go to Astrocade.com to join the waitlist and the discord.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
Episode Highlights:
- Grok 2's beta release features new image generation using Black Forest Labs' tech.
- Google introduces Gemini Voice Chat Mode available to subscribers and integrates it into Pixel Buds Pro 2.
- Huawei's Ascend 910C AI chip aims to rival NVIDIA's H100 amidst US export controls.
- Overview of potential risks of unaligned AI models and skepticism around SingularityNet's AGI supercomputer claims.
Timestamps + Links:
- (00:00:00) Intro / Banter
- (00:02:15) Response to listener comments / corrections
- Tools & Apps
- (00:04:24) Grok-2 is out in beta, now with added AI image generation
- (00:11:28) OpenAI reveals an updated GPT-4o model - but can't quite explain how it's better
- (00:13:48) Google Gemini’s voice chat mode is here
- (00:16:18) Google’s Pixel Buds Pro 2 bring Gemini to your ears
- (00:19:55) Google’s AI-generated search summaries change how they show their sources
- (00:23:13) Prompt Caching is Now Available on the Anthropic API for Specific Claude Models
- Applications & Business
- (00:26:56) Meet Black Forest Labs, the startup powering Elon Musk’s unhinged AI image generator
- (00:26:56) Huawei readies new AI chip to challenge Nvidia in China, WSJ reports
- (00:37:53) ASML and Imec Announce High-NA Lithography Breakthrough
- (00:43:07) Chinese startup WeRide gets nod to test robotaxis with passengers in California
- (00:45:49) Perplexity’s popularity surges as AI search start-up takes on Google
- (00:51:55) Lisa Su formally welcomes Silo AI team to AMD after completing $665 million acquisition
- Projects & Open Source
- (00:54:31) FalconMamba 7B Released: The World’s First Attention-Free AI Model with 5500GT Training Data and 7 Billion Parameters
- (00:59:25) OpenAI has introduced SWE-bench Verified to evaluate AI performance
- (01:04:21) Nous Research presents Hermes 3
- (01:11:07) New supercomputing network could lead to AGI, scientists hope, with 1st node coming online within weeks
- Research & Advancements
- (01:14:40) The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
- (01:30:24) Imagen 3
- (01:32:48) The Data Addition Dilemma
- (01:37:35) LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs
- Policy & Safety
- Synthetic Media & Art
- (01:56:21) AI Song Outro
#178 - More Not-Acquihires, More OpenAI drama, More LLM Scaling Talk
Our 178th episode with a summary and discussion of last week's big AI news!
NOTE: this is a re-upload with fixed audio, my bad on the last one! - Andrey
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
If you would like to get a sneak peek and help test Andrey's generative AI application, go to Astrocade.com to join the waitlist and the discord.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
In this episode: - Notable personnel movements and product updates, such as Character.ai leaders joining Google and new AI features in Reddit and Audible. - OpenAI's dramatic changes with co-founder exits, extended leaves, and new lawsuits from Elon Musk. - Rapid advancements in humanoid robotics exemplified by new models from companies like Figure in partnership with OpenAI, achieving amateur-level human performance in tasks like table tennis. - Research advancements such as Google's compute-efficient inference models and self-compressing neural networks, showcasing significant reductions in compute requirements while maintaining performance.
Timestamps + Links:
- (00:00:00) Intro / Banter
- (00:03:14) Response to listener comments / corrections
- Applications & Business
- (00:06:56) Google’s hiring of Character.AI’s founders is the latest sign that part of the AI startup world is starting to implode
- (00:15:12) Investors in Adept AI will be paid back after Amazon hires startup’s top talent
- (00:22:36) AI chip start-up Groq’s value rises to $2.8bn as it takes on Nvidia
- (00:29:22) OpenAI co-founder Schulman leaves for Anthropic, Brockman takes extended leave
- (00:36:18) Elon Musk files new lawsuit against OpenAI and Sam Altman
- (00:41:40) Figure’s new humanoid robot leverages OpenAI for natural speech conversations
- (00:47:01) ASML, Tokyo Electron dodge new US chip export rules, for now
- (00:53:10) OpenAI reportedly leads $60M round for webcam startup Opal
- Tools & Apps
- Research & Advancements
- (01:06:35) Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
- (01:16:27) Achieving Human Level Competitive Robot Table Tennis
- (01:20:19) Self-Compressing Neural Networks
- (01:28:30) Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models
- (01:32:43) Berkeley Humanoid: A Research Platform for Learning-based Control
- Policy & Safety
- (01:33:35) METR announces results of study on comparative capabilities of humans and agents
- (01:39:35) ‘The Godmother of AI’ says California’s well-intended AI bill will harm the U.S. ecosystem
- (01:49:13) Google Monopolized Search Through Illegal Deals, Judge Rules
- (01:54:56) Amazon faces UK merger probe over $4B Anthropic AI investment
- (01:55:44) GPT-4o System Card
- (02:03:09) Outro
#177 - Instagram AI Bots, Noam Shazeer -> Google, FLUX.1, SAM2
Our 177th episode with a summary and discussion of last week's big AI news!
NOTE: apologies for this episode again coming out about a week late, next one will be coming out soon...
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
If you'd like to listen to the interview with Andrey, check out https://www.superdatascience.com/podcast
If you would like to get a sneak peek and help test Andrey's generative AI application, go to Astrocade.com to join the waitlist and the discord.
In this episode, hosts Andrey Kurenkov and John Krohn dive into significant updates and discussions in the AI world, including Instagram's new AI features, Waymo's driverless cars rollout in San Francisco, and NVIDIA’s chip delays. They also review Meta's AI Studio, character.ai CEO Noam Shazir's return to Google, and Google's Gemini updates. Additional topics cover NVIDIA's hardware issues, advancements in humanoid robots, and new open-source AI tools like Open Devon. Policy discussions touch on the EU AI Act, the U.S. stance on open-source AI, and investigations into Google and Anthropic. The impact of misinformation via deepfakes, particularly one involving Elon Musk, is also highlighted, all emphasizing significant industry effects and regulatory implications.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
- (00:00:00) AI Song / Intro Banter
- (00:05:32) Response to listener comments / corrections
- Tools & Apps
- (00:10:16) Apple Intelligence to Miss Initial Launch of Upcoming iOS 18 Overhaul
- (00:16:35) Instagram starts letting people create AI versions of themselves
- Lighting round
- Applications & Business
- (00:31:44) Character.AI CEO Noam Shazeer returns to Google
- (00:39:41) Perplexity is cutting checks to publishers following plagiarism accusations
- Lighting round
- Projects & Open Source
- Research & Advancements
- Policy & Safety
- (01:50:10) AI Outro
#176 - SearchGPT, Gemini 1.5 Flash, Lamma 3.1 405B, Mistral Large 2
Our 176th episode with a summary and discussion of last week's big AI news!
NOTE: apologies for this episode coming out about a week late, things got in the way of editing it...
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
- (00:00:00) Intro Song
- (00:00:34) Intro Banter
- Tools & Apps
- (00:03:39) OpenAI announces SearchGPT, its AI-powered search engine
- (00:08:03) Google gives free Gemini users access to its faster, lighter 1.5 Flash AI model
- (00:09:10) X launches underwhelming Grok-powered ‘More About This Account’ feature
- (00:11:36) Kuaishou Launches Full Beta Testing for 'Kling AI' to Global Users, Elevates Model Capabilities
- (00:13:39) Adobe rolls out more generative AI features to Illustrator and Photoshop
- (00:14:25) Meta AI gets new ‘Imagine me’ selfie feature
- Projects & Open Source
- (00:15:19) Meta releases open-source AI model it says rivals OpenAI, Google tech
- (00:28:23) Mistral AI Unveils Mistral Large 2, Beats Llama 3.1 on Code and Math
- (00:34:00) Groq’s open-source Llama AI model tops leaderboard, outperforming GPT-4o and Claude in function calling
- (00:36:35) Apple shows off open AI prowess: new models outperform Mistral and Hugging Face offerings
- Applications & Business
- (00:40:25) Elon Musk wants Tesla to invest $5 billion into his newest startup, xAI — if shareholders approve
- (00:43:01) Nvidia said to be prepping Blackwell GPUs for Chinese market
- (00:46:28) Toronto AI company Cohere to indemnify customers who are sued for any copyright violations
- (00:49:09) AI startup Cohere raises US$500-million, valuing company at US$5.5-billion
- Research & Advancements
- Policy & Safety
- (01:02:56) Improving Model Safety Behavior with Rule-Based Rewards
- (01:06:39) Senators demand OpenAI detail efforts to make its AI safe
- (01:10:59) OpenAI reassigns top AI safety executive Aleksandr Madry to role focused on AI reasoning
- (01:13:08) As new tech threatens jobs, Silicon Valley promotes no-strings cash aid
- (01:17:33) Democratic senators seek to reverse Supreme Court ruling that restricts federal agency power
- Synthetic Media & Art
- (01:23:03) Outro
- (01:23:58) AI Song
#175 - GPT-4o Mini, OpenAI's Strawberry, Mixture of A Million Experts
Our 175th episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
In this episode of Last Week in AI, hosts Andrey Kurenkov and Jeremy Harris explore recent AI advancements including OpenAI's release of GPT 4.0 Mini and Mistral’s open-source models, covering their impacts on affordability and performance. They delve into enterprise tools for compliance, text-to-video models like Hyper 1.5, and YouTube Music enhancements. The conversation further addresses AI research topics such as the benefits of numerous small expert models, novel benchmarking techniques, and advanced AI reasoning. Policy issues including U.S. export controls on AI technology to China and internal controversies at OpenAI are also discussed, alongside Elon Musk's supercomputer ambitions and OpenAI’s Prover-Verify Games initiative.Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
Timestamps + links:
- (00:00:00) AI Song Intro
- (00:00:40) Intro / Banter
- Tools & Apps
- (00:03:57) OpenAI unveils GPT-4o mini, a small AI model powering ChatGPT
- (00:11:38) Meet Haiper 1.5, the new AI video generation model challenging Sora, Runway
- (00:16:32) Anthropic releases Claude app for Android
- (00:18:59) Google Vids is available to test out Gemini AI-created video presentations
- (00:20:27) YouTube Music sound search rolling out, AI ‘conversational radio’ in testing
- Applications & Business
- (00:23:30) OpenAI working on new reasoning technology under code name ‘Strawberry’
- (00:30:45) Inside Elon Musk’s Mad Dash To Build A Giant xAI Supercomputer In Memphis
- (00:37:15) Apple, NVIDIA and Anthropic reportedly used YouTube transcripts without permission to train AI models
- (00:41:05) After Tesla and OpenAI, Andrej Karpathy’s startup aims to apply AI assistants to education
- (00:43:40) Menlo Ventures and Anthropic team up on a $100M AI fund
- Projects & Open Source
- (00:46:27) Mistral releases Codestral Mamba for faster, longer code generation
- (00:50:36) Mistral AI and NVIDIA Unveil Mistral NeMo 12B, a Cutting-Edge Enterprise AI Model
- (00:52:51) Hugging Face Releases SmoLLM, a Series of Small Language Models, Beats Qwen2 and Phi 1.5
- (00:56:11) Stable Diffusion 3 License Revamped Amid Blowback, Promising Better Model
- Research & Advancements
- Policy & Safety
- (01:20:50) Prover-Verifier Games improve legibility of language model outputs
- (01:28:05) Trump allies draft AI order to launch ‘Manhattan Projects’ for defense
- (01:34:40) On scalable oversight with weak LLMs judging strong LLMs
- (01:36:24) Google, Microsoft offer Nvidia chips to Chinese companies, the Information reports
- (01:38:26) U.S. planning 'draconian' sanctions against China's semiconductor industry: Report
- (01:48:47) OpenAI illegally barred staff from airing safety risks, whistleblowers say
- (01:44:59) Outro + AI Song
#174 - Odyssey Text-to-Video, Groq LLM Engine, OpenAI Security Issues
Our 174rd episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
In this episode of Last Week in AI, we delve into the latest advancements and challenges in the AI industry, highlighting new features from Figma and Quora, regulatory pressures on OpenAI, and significant investments in AI infrastructure. Key topics include AMD's acquisition of Silo AI, Elon Musk's GPU cluster plans for XAI, unique AI model training methods, and the nuances of AI copying and memory constraints. We discuss developments in AI's visual perception, real-time knowledge updates, and the need for transparency and regulation in AI content labeling and licensing.
See full episode notes here.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
Timestamps + links:
- (00:00:00) Intro AI Song
- (00:00:41) Pre News Banter
- Tools & Apps
- (00:07:09) Odyssey Building 'Hollywood-Grade' AI Text-to-Video Model to Compete With Sora, Gen-3 Alpha
- (00:10:28) Anthropic’s Claude adds a prompt playground to quickly improve your AI apps
- (00:15:06) Figma pauses its new AI feature after Apple controversy
- (00:18:30) Quora’s Poe now lets users create and share web apps
- (00:20:54) Suno launches iPhone app — now you can make AI music on the go
- Applications & Business
- (00:21:42) Groq unveils lightning-fast LLM engine; developer base rockets past 280K in 4 months
- (00:27:03) Microsoft and Apple ditch OpenAI board seats amid regulatory scrutiny
- (00:29:39) OpenAI and Arianna Huffington are working together on an ‘AI health coach’
- (00:33:38) AI coding startup Magic seeks $1.5-billion valuation in new funding round, sources say
- (00:37:01) Sequoia and Andreessen Horowitz Clash Over AI Chip Supplies Amid Gen AI Boom
- (00:43:30) Elon Musk Reveals Plans To Make World’s “Most Powerful” 100,000 NVIDIA GPU AI Cluster
- (00:46:25) AMD plans to acquire Silo AI in $665 million deal
- (00:48:00) AI robotics startup raises US$300 million, including from Jeff Bezos
- (00:52:11) Intel begins groundwork on Magdeburg chip fab despite 13 remaining regulatory and environmental objections
- Research & Advancements
- (00:55:21) Learning to (Learn at Test Time): RNNs with Expressive Hidden States
- (01:03:12) Data curation via joint example selection further accelerates multimodal learning
- (01:09:11) CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation
- (01:13:25) Just read twice: closing the recall gap for recurrent language models
- (01:15:25) CodeUpdateArena: Benchmarking Knowledge Editing on API Updates
- (01:18:31) Composable Interventions for Language Models
- (01:24:09) Mind-reading AI recreates what you're looking at with amazing accuracy
- Policy & Safety
- (01:26:49) Covert Malicious Finetuning
- (01:31:23) OpenAI’s week of security issues
- (01:36:39) Here’s how OpenAI will determine how powerful its AI systems are
- (01:39:56) Me, Myself and AI: The Situational Awareness Dataset for LLMs
- (01:44:34) Exclusive: OpenAI partners with Los Alamos to study AI in the lab
- (01:47:36) Judge dismisses coders’ DMCA claims against Microsoft, OpenAI and GitHub
- (01:49:55) A former OpenAI safety employee said he quit because the company's leaders were 'building the Titanic' and wanted 'newer, shinier' things to sell
- Synthetic Media & Art
- (02:02:05) Outro + AI Song
#173 - Gemini Pro, Llama 400B, Gen-3 Alpha, Moshi, Supreme Court
Our 173rd episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
See full episode notes here.
Read out our text newsletter and comment on the podcast at https://lastweekin.ai/
If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form.
Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
In this episode of Last Week in AI, we explore the latest advancements and debates in the AI field, including Google's release of Gemini 1.5, Meta's upcoming LLaMA 3, and Runway's Gen 3 Alpha video model. We discuss emerging AI features, legal disputes over data usage, and China's competition in AI. The conversation spans innovative research developments, cost considerations of AI architectures, and policy changes like the U.S. Supreme Court striking down Chevron deference. We also cover U.S. export controls on AI chips to China, workforce development in the semiconductor industry, and Bridgewater's new AI-driven financial fund, evaluating the broader financial and regulatory impacts of AI technologies.Timestamps + links:
- (00:00:00) Intro / Banter
- Tools & Apps
- (00:03:24) Google opens up Gemini 1.5 Flash, Pro with 2M tokens to the public
- (00:08:47) Meta is about to launch its biggest Llama model yet — here’s why it’s a big deal
- (00:12:38) Runway’s Gen-3 Alpha AI video model now available – but there’s a catch
- (00:16:28) This is Google AI, and it's coming to the Pixel 9
- (00:17:30) AI Firm ElevenLabs Sets Audio Reader Pact With Judy Garland, James Dean, Burt Reynolds and Laurence Olivier Estates
- (00:20:06) Perplexity’s ‘Pro Search’ AI upgrade makes it better at math and research
- (00:23:12) Gemini’s data-analyzing abilities aren’t as good as Google claims
- Applications & Business
- (00:26:38) Quora’s Chatbot Platform Poe Allows Users to Download Paywalled Articles on Demand
- (00:32:04) Huawei and Wuhan Xinxin to develop high-bandwidth memory chips amid US restrictions
- (00:34:57) Alibaba’s large language model tops global ranking of AI developer platform Hugging Face
- (00:39:01) Here comes a Meta Ray-Bans challenger with ChatGPT-4o and a camera
- (00:43:35) Apple’s Phil Schiller is reportedly joining OpenAI’s board
- (00:47:26) AI Video Startup Runway Looking to Raise $450 Million
- Projects & Open Source
- (00:48:10) Kyutai Open Sources Moshi: A Real-Time Native Multimodal Foundation AI Model that can Listen and Speak
- (00:50:44) MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation
- (00:53:47) Anthropic Pushes for Third-Party AI Model Evaluations
- (00:57:29) Mozilla Llamafile, Builders Projects Shine at AI Engineers World's Fair
- Research & Advancements
- (00:59:26) Researchers upend AI status quo by eliminating matrix multiplication in LLMs
- (01:05:55) AI Agents That Matter
- (01:12:09) WARP: On the Benefits of Weight Averaged Rewarded Policies
- (01:17:20) Scaling Synthetic Data Creation with 1,000,000,000 Personas
- (01:24:16) Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization
- Policy & Safety
- (01:26:32) With Chevron’s demise, AI regulation seems dead in the water
- (01:33:40) Nvidia to make $12bn from AI chips in China this year despite US controls
- (01:37:52) Uncle Sam relies on manual processes to oversee restrictions on Huawei, other Chinese tech players
- (01:40:57) U.S. government addresses critical workforce shortages for the semiconductor industry with new program
- (01:42:42) Bridgewater starts $2 billion fund that uses machine learning for decision-making and will include models from OpenAI, Anthropic and Perplexity
- (01:47:57) Outro
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