The end of classical computer science is coming, and most of us are dinosaurs waiting for the meteor to hit, says Matt Welsh.

"I came of age in the 1980s, programming personal computers like the Commodore VIC-20 and Apple IIe at home. Going on to study computer science in college and ultimately getting a PhD at Berkeley, the bulk of my professional training was rooted in what I will call 'classical' CS: programming, algorithms, data structures, systems, programming languages."

"When I was in college in the early '90s, we were still in the depth of the AI Winter, and AI as a field was likewise dominated by classical algorithms. In Dan Huttenlocher's PhD-level computer vision course in 1995 or so, we never once discussed anything resembling deep learning or neural networks--it was all classical algorithms like Canny edge detection, optical flow, and Hausdorff distances."

"One thing that has not really changed is that computer science is taught as a discipline with data structures, algorithms, and programming at its core. I am going to be amazed if in 30 years, or even 10 years, we are still approaching CS in this way. Indeed, I think CS as a field is in for a pretty major upheaval that few of us are really prepared for."

"I believe that the conventional idea of 'writing a program' is headed for extinction, and indeed, for all but very specialized applications, most software, as we know it, will be replaced by AI systems that are trained rather than programmed."

"I'm not just talking about CoPilot replacing programmers. I'm talking about replacing the entire concept of writing programs with training models. In the future, CS students aren't going to need to learn such mundane skills as how to add a node to a binary tree or code in C++. That kind of education will be antiquated, like teaching engineering students how to use a slide rule."

"The shift in focus from programs to models should be obvious to anyone who has read any modern machine learning papers. These papers barely mention the code or systems underlying their innovations; the building blocks of AI systems are much higher-level abstractions like attention layers, tokenizers, and datasets."

This got me thinking: Over the last 20 years, I've been predicting AI would advance to the point where it could automate jobs, and it's looking more and more like I was fundamentally right about that, and all the people who poo-poo'd the idea over the years in coversations with me were wrong. But while I was right about that fundamental idea (and right that there wouldn't be "one AI in a box" that anyone could pull the plug on if something went wrong, but a diffusion of the technology around the world like every previous technology), I was wrong about how exactly it would play out.

First I was wrong about the timescales: I thought it would be necessary to understand much more about how the brain works, and to work algorithms derived from neuroscience into AI models, and looking at the rate of advancement in neuroscience I predicted AI wouldn't be in its current state for a long time. While broad concepts like "neuron" and "attention" have been incorporated into AI, there are practically no specific algorithms that have been ported from brains to AI systems.

Second, I was wrong about what order. I was wrong in thinking "routine" jobs would be automated first, and "creative" jobs last. It turns out that what matters is "mental" vs "physical". Computers can create visual art and music just by thinking very hard -- it's a purely "mental" activity, and computers can do all that thinking in bits and bytes.

This has led me to ponder: What occupations require the greatest level of manual dexterity?

Those should be the jobs safest from the AI revolution.

The first that came to mind for me -- when I was trying to think of jobs that require an extreme level of physical dexterity and pay very highly -- was "surgeon". So I now predict "surgeon" will be the last job to get automated. If you're giving career advice to a young person (or you are a young person), the advice to give is: become a surgeon.

Other occupations safe (for now) against automation, for the same reason would include "physical therapist", "dentist", "dental hygienist", "dental technician", "medical technician" (e.g. those people who customize prosthetics, orthodontic devices, and so on), and so on. "Nurse" who routinely does physical procedures like drawing blood.

Continuing in the same vein but going outside the medical field (pun not intended but allowed to stand once recognized), I'd put "electronics technician". I don't think robots will be able to solder any time soon, or manipulate very small components, at least after the initial assembly is completed which does seem to be highly amenable to automation. But once electronic components fail, to the extent it falls on people to repair them, rather than throw them out and replace them (which admittedly happens a lot), humans aren't going to be replaced any time soon.

Likewise "machinist" who works with small parts and tools.

"Engineer" ought to be ok -- as long as they're mechanical engineers or civil engineers. Software engineers are in the crosshairs. What matters is whether physical manipulation is part of the job.

"Construction worker" -- some jobs are high pay/high skill while others are low pay/low skill. Will be interesting to see what gets automated first and last in construction.

Other "trade" jobs like "plumber", "electrician", "welder" -- probably safe for a long time.

"Auto mechanic" -- probably one of the last jobs to be automated. The factory where the car is initially manufacturered, a very controlled environment, may be full of robots, but it's hard to see robots extending into the auto mechanic's shop where cars go when they break down.

"Jewler" ought to be a safe job for a long time. "Watchmaker" (or "watch repairer") -- I'm still amazed people pay so much for old-fashioned mechanical watches. I guess the point is to be pieces of jewlry, so these essentially count as "jewler" jobs.

"Tailor" and "dressmaker" and other jobs centered around sewing.

"Hairstylist" / "barber" -- you probably won't be trusting a robot with scissors close to your head any time soon.

"Chef", "baker", whatever the word is for "cake calligrapher". Years ago I thought we'd have automated kitchens at fast food restaurants by now but they are no where in sight. And nowhere near automating the kitchens of the fancy restaurants with the top chefs.

Finally, let's revisit "artist". While "artist" is in the crosshairs of AI, some "artist" jobs are actually physical -- such as "sculptor" and "glassblower". These might be resistant to AI for a long time. Not sure how many sculptors and glassblowers the economy can support, though. Might be tough if all the other artists stampede into those occupations.

While "musician" is totally in the crosshairs of AI, as we see, that applies only to musicians who make recorded music -- going "live" may be a way to escape the automation. No robots with the manual dexterity to play physical guitars, violins, etc, appear to be on the horizon. Maybe they can play drums?

And finally for my last item: "Magician" is another live entertainment career that requires a lot of manual dexterity and that ought to be hard for a robot to replicate. For those of you looking for a career in entertainment. Not sure how many magicians the economy can support, though.

The end of programming - Matt Welsh

#solidstatelife #genai #codingai #technologicalunemployment

"In defense of AI art".

YouTuber "LiquidZulu" makes a gigantic video aimed at responding once and for all to all possible arguments against AI art.

His primary argument seems to me to be that AI art systems are learning art in a manner analogous to human artists -- by learning from examples from other artists -- and do not plagiarize because they do not copy exactly any artists' work. In contrast AI art systems are actually good at combining styles in new ways. Therefore, AI art generators are just as valid "artists" as any human artists.

Artists have no right to government protection from getting their jobs get replaced by technology, he says, because nobody anywhere else in the economy has any right to government protection to getting their jobs replaced by technology.

On the flip side, he thinks the ability of AI art generators to bring the ability to create art to the masses is a good thing that should be celebrated.

Below-average artists have no right to deprive people of this ability to generate the art they like because those low-quality artists want to be paid.

Apparently he considers himself an anarcho-capitalist (something he has in common with... nobody here?) and has has harsh words for people he considers neo-Luddites. He accuses artists complaining about AI art generators of being "elitist".

In defense of AI art - LiquidZulu

#solidstatelife #ai #genai #aiart #aiethics

For the first time, Alice Yalcin Efe is scared of AI as a music producer.

A professional music producer, been number one on BeatPort, has millions of streams on Spotify, played in big festivals and clubs, "yet for the first time I am scared of AI as a music producer."

When you're homeless, you can listen to AI mix the beat on the beach.

After that, she ponders what this means for all the rest of us. Those of us who aren't professional music producers. Well, I guess we can all be music producers now.

"Music on demand becomes literal. You feel heartbroken, type it in. Type in the genres that you want. Type in the lyrics that you want. Type in the mood that you want and then AI spits out the perfect ballad for you to listen."

"I think it's both incredible and horrifying at the same time. I honestly don't know what comes next. Will this kill the artists' soul, or will it give us just more tools to make even greater things?"

For the first time, I'm scared of AI as a music producer - Alice Yalcin Efe - Mercurial Tones Academy

#solidstatelife #ai #genai #musicai

Musician Paul Folia freaks out over Suno and Udio (and other music AI). Reminds me of the freak-out of visual artists a year ago. It appears AI is going to replace humans one occupation at a time and people will freak out when it's their turn. He estimates in a year AI music will be of high enough quality to wipe out stock music writing completely, producing tracks for a price no human can compete with ($0.02 and in minutes).

He experiments with various music styles an artists' styles and the part that impressed me the most was, perhaps surprisingly, the baroque music. After noting that the training data was probably easy to get because it's public domain, he says, "This m-f-er learned some serious harmony. Not like three chords and some singing."

Suno, Udio (and other music AI). We're f*ed and it's really bad. Seriously. - Folia Soundstudio

#solidstatelife #ai #genai #musicai

"Evaluate LLMs in real time with Street Fighter III"

"A new kind of benchmark? Street Fighter III assesses the ability of LLMs to understand their environment and take actions based on a specific context. As opposed to RL models, which blindly take actions based on the reward function, LLMs are fully aware of the context and act accordingly."

"Each player is controlled by an LLM. We send to the LLM a text description of the screen. The LLM decide on the next moves its character will make. The next moves depends on its previous moves, the moves of its opponents, its power and health bars."

"Fast: It is a real time game, fast decisions are key"
"Smart: A good fighter thinks 50 moves ahead"
"Out of the box thinking: Outsmart your opponent with unexpected moves"
"Adaptable: Learn from your mistakes and adapt your strategy"
"Resilient: Keep your RPS high for an entire game"

Um... Alrighty then...

OpenGenerativeAI / llm-colosseum

#solidstatelife #ai #genai #llms

Creating sexually explicit deepfakes to become a criminal offence in the UK. If the images or videos were never intended to be shared, under the new legislation, the person will face a criminal record and unlimited fine. If the images are shared, they face jail time.

Creating sexually explicit deepfakes to become a criminal offence

#solidstatelife #ai #genai #computervision #deepfakes #aiethics

The 2024 AI Index Report from Stanford's Human-Centered Artificial Intelligence lab.

It says between 2010 and 2022, the number of AI research papers per year nearly tripled, from 88,000 to 240,000. So if you're wondering why I'm always behind in my reading of AI research papers, well, there's your answer.

Besides that, I'm just going to quote from the highlights in the report itself, because it seems I can't improve on them, at least not in short order and I've decided I'd like to get this report out to you all quickly. I'll continue browsing through the charts & graphs in all the chapters, but for now I'll just give you their highlights and you can decide if you want to download the report and read it or part of it more thoroughly.

"Chapter 1: Research and Development"

"1. Industry continues to dominate frontier AI research. In 2023, industry produced 51 notable machine learning models, while academia contributed only 15. There were also 21 notable models resulting from industry-academia collaborations in 2023, a new high."

"2. More foundation models and more open foundation models. In 2023, a total of 149 foundation models were released, more than double the amount released in 2022. Of these newly released models, 65.7% were open-source, compared to only 44.4% in 2022 and 33.3% in 2021."

"3. Frontier models get way more expensive. According to AI Index estimates, the training costs of state-of-the-art AI models have reached unprecedented levels. For example, OpenAI's GPT-4 used an estimated $78 million worth of compute to train, while Google's Gemini Ultra cost $191 million for compute."

"4. The United States leads China, the EU, and the UK as the leading source of top AI models. In 2023, 61 notable AI models originated from US-based institutions, far outpacing the European Union's 21 and China's 15."

"5. The number of AI patents skyrockets. From 2021 to 2022, AI patent grants worldwide increased sharply by 62.7%. Since 2010, the number of granted AI patents has increased more than 31 times."

"6. China dominates AI patents. In 2022, China led global AI patent origins with 61.1%, significantly outpacing the United States, which accounted for 20.9% of AI patent origins. Since 2010, the US share of AI patents has decreased from 54.1%."

"7. Open-source AI research explodes. Since 2011, the number of AI-related projects on GitHub has seen a consistent increase, growing from 845 in 2011 to approximately 1.8 million in 2023. Notably, there was a sharp 59.3% rise in the total number of GitHub AI projects in 2023 alone. The total number of stars for AI-related projects on GitHub also significantly increased in 2023, more than tripling from 4.0 million in 2022 to 12.2 million."

"8. The number of AI publications continues to rise. Between 2010 and 2022, the total number of AI publications nearly tripled, rising from approximately 88,000 in 2010 to more than 240,000 in 2022. The increase over the last year was a modest 1.1%."

"Chapter 2: Technical Performance"

"1. AI beats humans on some tasks, but not on all. AI has surpassed human performance on several benchmarks, including some in image classification, visual reasoning, and English understanding. Yet it trails behind on more complex tasks like competition-level mathematics, visual commonsense reasoning and planning."

"2. Here comes multimodal AI. Traditionally AI systems have been limited in scope, with language models excelling in text comprehension but faltering in image processing, and vice versa. However, recent advancements have led to the development of strong multimodal models, such as Google's Gemini and OpenAI's GPT-4. These models demonstrate flexibility and are capable of handling images and text and, in some instances, can even process audio."

"3. Harder benchmarks emerge. AI models have reached performance saturation on established benchmarks such as ImageNet, SQuAD, and SuperGLUE, prompting researchers to develop more challenging ones. In 2023, several challenging new benchmarks emerged, including SWE-bench for coding, HEIM for image generation, MMMU for general reasoning, MoCa for moral reasoning, AgentBench for agent-based behavior, and HaluEval for hallucinations."

"4. Better AI means better data which means ... even better AI. New AI models such as SegmentAnything and Skoltech are being used to generate specialized data for tasks like image segmentation and 3D reconstruction. Data is vital for AI technical improvements. The use of AI to create more data enhances current capabilities and paves the way for future algorithmic improvements, especially on harder tasks."

"5. Human evaluation is in. With generative models producing high-quality text, images, and more, benchmarking has slowly started shifting toward incorporating human evaluations like the Chatbot Arena Leaderboard rather than computerized rankings like ImageNet or SQuAD. Public sentiment about AI is becoming an increasingly important consideration in tracking AI progress."

"6. Thanks to LLMs, robots have become more flexible. The fusion of language modeling with robotics has given rise to more flexible robotic systems like PaLM-E and RT-2. Beyond their improved robotic capabilities, these models can ask questions, which marks a significant step toward robots that can interact more effectively with the real world."

"7. More technical research in agentic AI. Creating AI agents, systems capable of autonomous operation in specific environments, has long challenged computer scientists. However, emerging research suggests that the performance of autonomous AI agents is improving. Current agents can now master complex games like Minecraft and effectively tackle real-world tasks, such as online shopping and research assistance."

"8. Closed LLMs significantly outperform open ones. On 10 select AI benchmarks, closed models outperformed open ones, with a median performance advantage of 24.2%. Differences in the performance of closed and open models carry important implications for AI policy debates."

"Chapter 3: Responsible AI"

"1. Robust and standardized evaluations for LLM responsibility are seriously lacking. New research from the AI Index reveals a significant lack of standardization in responsible AI reporting. Leading developers, including OpenAI, Google, and Anthropic, primarily test their models against different responsible AI benchmarks. This practice complicates efforts to systematically compare the risks and limitations of top AI models."

"2. Political deepfakes are easy to generate and difficult to detect. Political deepfakes are already affecting elections across the world, with recent research suggesting that existing AI deepfake methods perform with varying levels of accuracy. In addition, new projects like CounterCloud demonstrate how easily AI can create and disseminate fake content."

"3. Researchers discover more complex vulnerabilities in LLMs. Previously, most efforts to red team AI models focused on testing adversarial prompts that intuitively made sense to humans. This year, researchers found less obvious strategies to get LLMs to exhibit harmful behavior, like asking the models to infinitely repeat random words."

"4. Risks from AI are becoming a concern for businesses across the globe. A global survey on responsible AI highlights that companies' top AI-related concerns include privacy, data security, and reliability. The survey shows that organizations are beginning to take steps to mitigate these risks. Globally, however, most companies have so far only mitigated a small portion of these risks."

"5. LLMs can output copyrighted material. Multiple researchers have shown that the generative outputs of popular LLMs may contain copyrighted material, such as excerpts from The New York Times or scenes from movies. Whether such output constitutes copyright violations is becoming a central legal question."

"6. AI developers score low on transparency, with consequences for research. The newly introduced Foundation Model Transparency Index shows that AI developers lack transparency, especially regarding the disclosure of training data and methodologies. This lack of openness hinders efforts to further understand the robustness and safety of AI systems."

"7. Extreme AI risks are difficult to analyze. Over the past year, a substantial debate has emerged among AI scholars and practitioners regarding the focus on immediate model risks, like algorithmic discrimination, versus potential long-term existential threats. It has become challenging to distinguish which claims are scientifically founded and should inform policymaking. This difficulty is compounded by the tangible nature of already present short-term risks in contrast with the theoretical nature of existential threats."

"8. The number of AI incidents continues to rise. According to the AI Incident Database, which tracks incidents related to the misuse of AI, 123 incidents were reported in 2023, a 32.3 percentage point increase from 2022. Since 2013, AI incidents have grown by over twentyfold. A notable example includes AI-generated, sexually explicit deepfakes of Taylor Swift that were widely shared online."

"9. ChatGPT is politically biased. Researchers find a significant bias in ChatGPT toward Democrats in the United States and the Labour Party in the UK. This finding raises concerns about the tool's potential to influence users' political views, particularly in a year marked by major global elections."

"Chapter 4: Economy"

"1. Generative AI investment skyrockets. Despite a decline in overall AI private investment last year, funding for generative AI surged, nearly octupling from 2022 to reach $25.2 billion. Major players in the generative AI space, including OpenAI, Anthropic, Hugging Face, and Inflection, reported substantial fundraising rounds."

"2. Already a leader, the United States pulls even further ahead in AI private investment. In 2023, the United States saw AI investments reach $67.2 billion, nearly 8.7 times more than China, the next highest investor. While private AI investment in China and the European Union, including the United Kingdom, declined by 44.2% and 14.1%, respectively, since 2022, the United States experienced a notable increase of 22.1% in the same time frame."

"3. Fewer AI jobs in the United States and across the globe. In 2022, AI-related positions made up 2.0% of all job postings in America, a figure that decreased to 1.6% in 2023. This decline in AI job listings is attributed to fewer postings from leading AI firms and a reduced proportion of tech roles within these companies."

"4. AI decreases costs and increases revenues. A new McKinsey survey reveals that 42% of surveyed organizations report cost reductions from implementing AI (including generative AI), and 59% report revenue increases. Compared to the previous year, there was a 10 percentage point increase in respondents reporting decreased costs, suggesting AI is driving significant business efficiency gains."

"5. Total AI private investment declines again, while the number of newly funded AI companies increases. Global private AI investment has fallen for the second year in a row, though less than the sharp decrease from 2021 to 2022. The count of newly funded AI companies spiked to 1,812, up 40.6% from the previous year."

"6. AI organizational adoption ticks up. A 2023 McKinsey report reveals that 55% of organizations now use AI (including generative AI) in at least one business unit or function, up from 50% in 2022 and 20% in 2017."

"7. China dominates industrial robotics. Since surpassing Japan in 2013 as the leading installer of industrial robots, China has significantly widened the gap with the nearest competitor nation. In 2013, China's installations accounted for 20.8% of the global total, a share that rose to 52.4% by 2022."

"8. Greater diversity in robot installations. In 2017, collaborative robots represented a mere 2.8% of all new industrial robot installations, a figure that climbed to 9.9% by 2022. Similarly, 2022 saw a rise in service robot installations across all application categories, except for medical robotics. This trend indicates not just an overall increase in robot installations but also a growing emphasis on deploying robots for human-facing roles."

"9. The data is in: AI makes workers more productive and leads to higher quality work. In 2023, several studies assessed AI's impact on labor, suggesting that AI enables workers to complete tasks more quickly and to improve the quality of their output. These studies also demonstrated AI's potential to bridge the skill gap between low- and high-skilled workers. Still, other studies caution that using AI without proper oversight can lead to diminished performance."

"10. Fortune 500 companies start talking a lot about AI, especially generative AI. In 2023, AI was mentioned in 394 earnings calls (nearly 80% of all Fortune 500 companies), a notable increase from 266 mentions in 2022. Since 2018, mentions of AI in Fortune 500 earnings calls have nearly doubled. The most frequently cited theme, appearing in 19.7% of all earnings calls, was generative AI."

"Chapter 5: Science and Medicine"

"1. Scientific progress accelerates even further, thanks to AI. In 2022, AI began to advance scientific discovery. 2023, however, saw the launch of even more significant science-related AI applications-- from AlphaDev, which makes algorithmic sorting more efficient, to GNoME, which facilitates the process of materials discovery."

"2. AI helps medicine take significant strides forward. In 2023, several significant medical systems were launched, including EVEscape, which enhances pandemic prediction, and AlphaMissence, which assists in AI-driven mutation classification. AI is increasingly being utilized to propel medical advancements."

"3. Highly knowledgeable medical AI has arrived. Over the past few years, AI systems have shown remarkable improvement on the MedQA benchmark, a key test for assessing AI's clinical knowledge. The standout model of 2023, GPT-4 Medprompt, reached an accuracy rate of 90.2%, marking a 22.6 percentage point increase from the highest score in 2022. Since the benchmark's introduction in 2019, AI performance on MedQA has nearly tripled."

"4. The FDA approves more and more AI-related medical devices. In 2022, the FDA approved 139 AI-related medical devices, a 12.1% increase from 2021. Since 2012, the number of FDA-approved AI-related medical devices has increased by more than 45-fold. AI is increasingly being used for real-world medical purposes."

"Chapter 6: Education"

"1. The number of American and Canadian CS bachelor's graduates continues to rise, new CS master's graduates stay relatively flat, and PhD graduates modestly grow. While the number of new American and Canadian bachelor's graduates has consistently risen for more than a decade, the number of students opting for graduate education in CS has flattened. Since 2018, the number of CS master's and PhD graduates has slightly declined."

"2. The migration of AI PhDs to industry continues at an accelerating pace. In 2011, roughly equal percentages of new AI PhDs took jobs in industry (40.9%) and academia (41.6%). However, by 2022, a significantly larger proportion (70.7%) joined industry after graduation compared to those entering academia (20.0%). Over the past year alone, the share of industry-bound AI PhDs has risen by 5.3 percentage points, indicating an intensifying brain drain from universities into industry."

"3. Less transition of academic talent from industry to academia. In 2019, 13% of new AI faculty in the United States and Canada were from industry. By 2021, this figure had declined to 11%, and in 2022, it further dropped to 7%. This trend indicates a progressively lower migration of high-level AI talent from industry into academia."

"4. CS education in the United States and Canada becomes less international. Proportionally fewer international CS bachelor's, master's, and PhDs graduated in 2022 than in 2021. The drop in international students in the master's category was especially pronounced."

"5. More American high school students take CS courses, but access problems remain. In 2022, 201,000 AP CS exams were administered. Since 2007, the number of students taking these exams has increased more than tenfold. However, recent evidence indicates that students in larger high schools and those in suburban areas are more likely to have access to CS courses."

"6. AI-related degree programs are on the rise internationally. The number of English-language, AI-related postsecondary degree programs has tripled since 2017, showing a steady annual increase over the past five years. Universities worldwide are offering more AI-focused degree programs."

"7. The United Kingdom and Germany lead in European informatics, CS, CE, and IT graduate production. The United Kingdom and Germany lead Europe in producing the highest number of new informatics, CS, CE, and information bachelor's, master's, and PhD graduates. On a per capita basis, Finland leads in the production of both bachelor's and PhD graduates, while Ireland leads in the production of master's graduates."

"Chapter 7: Policy and Governance"

"1. The number of AI regulations in the United States sharply increases. The number of AI-related regulations has risen significantly in the past year and over the last five years. In 2023, there were 25 AI-related regulations, up from just one in 2016. Last year alone, the total number of AI-related regulations grew by 56.3%."

"2. The United States and the European Union advance landmark AI policy action. In 2023, policymakers on both sides of the Atlantic put forth substantial proposals for advancing AI regulation The European Union reached a deal on the terms of the AI Act, a landmark piece of legislation enacted in 2024. Meanwhile, President Biden signed an Executive Order on AI, the most notable AI policy initiative in the United States that year."

"3. AI captures US policymaker attention. The year 2023 witnessed a remarkable increase in AI-related legislation at the federal level, with 181 bills proposed, more than double the 88 proposed in 2022."

"4. Policymakers across the globe cannot stop talking about AI. Mentions of AI in legislative proceedings across the globe have nearly doubled, rising from 1,247 in 2022 to 2,175 in 2023. AI was mentioned in the legislative proceedings of 49 countries in 2023. Moreover, at least one country from every continent discussed AI in 2023, underscoring the truly global reach of AI policy discourse."

"5. More regulatory agencies turn their attention toward AI. The number of US regulatory agencies issuing AI regulations increased to 21 in 2023 from 17 in 2022, indicating a growing concern over AI regulation among a broader array of American regulatory bodies. Some of the new regulatory agencies that enacted AIrelated regulations for the first time in 2023 include the Department of Transportation, the Department of Energy, and the Occupational Safety and Health Administration."

"Chapter 8: Diversity"

"1. US and Canadian bachelor's, master's, and PhD CS students continue to grow more ethnically diverse. While white students continue to be the most represented ethnicity among new resident graduates at all three levels, the representation from other ethnic groups, such as Asian, Hispanic, and Black or African American students, continues to grow. For instance, since 2011, the proportion of Asian CS bachelor's degree graduates has increased by 19.8 percentage points, and the proportion of Hispanic CS bachelor's degree graduates has grown by 5.2 percentage points."

"2. Substantial gender gaps persist in European informatics, CS, CE, and IT graduates at all educational levels. Every surveyed European country reported more male than female graduates in bachelor's, master's, and PhD programs for informatics, CS, CE, and IT. While the gender gaps have narrowed in most countries over the last decade, the rate of this narrowing has been slow."

"3. US K12 CS education is growing more diverse, reflecting changes in both gender and ethnic representation. The proportion of AP CS exams taken by female students rose from 16.8% in 2007 to 30.5% in 2022. Similarly, the participation of Asian, Hispanic/Latino/Latina, and Black/African American students in AP CS has consistently increased year over year."

"Chapter 9: Public Opinion"

"1. People across the globe are more cognizant of AI's potential impact--and more nervous. A survey from Ipsos shows that, over the last year, the proportion of those who think AI will dramatically affect their lives in the next three to five years has increased from 60% to 66%. Moreover, 52% express nervousness toward AI products and services, marking a 13 percentage point rise from 2022. In America, Pew data suggests that 52% of Americans report feeling more concerned than excited about AI, rising from 38% in 2022."

"2. AI sentiment in Western nations continues to be low, but is slowly improving. In 2022, several developed Western nations, including Germany, the Netherlands, Australia, Belgium, Canada, and the United States, were among the least positive about AI products and services. Since then, each of these countries has seen a rise in the proportion of respondents acknowledging the benefits of AI, with the Netherlands experiencing the most significant shift."

"3. The public is pessimistic about AI's economic impact. In an Ipsos survey, only 37% of respondents feel AI will improve their job. Only 34% anticipate AI will boost the economy, and 32% believe it will enhance the job market."

"4. Demographic differences emerge regarding AI optimism. Significant demographic differences exist in perceptions of AI's potential to enhance livelihoods, with younger generations generally more optimistic. For instance, 59% of Gen Z respondents believe AI will improve entertainment options, versus only 40% of baby boomers. Additionally, individuals with higher incomes and education levels are more optimistic about AI's positive impacts on entertainment, health, and the economy than their lower-income and less-educated counterparts."

"5. ChatGPT is widely known and widely used. An international survey from the University of Toronto suggests that 63% of respondents are aware of ChatGPT. Of those aware, around half report using ChatGPT at least once weekly."

AI Index Report 2024 -- Artificial Intelligence Index

#solidstatelife #ai #genai

"The rise of generative AI and 'deepfakes' -- or videos and pictures that use a person's image in a false way -- has led to the wide proliferation of unauthorized clips that can damage celebrities' brands and businesses."

"Talent agency WME has inked a partnership with Loti, a Seattle-based firm that specializes in software used to flag unauthorized content posted on the internet that includes clients' likenesses. The company, which has 25 employees, then quickly sends requests to online platforms to have those infringing photos and videos removed."

This company Loti has a product called "Watchtower", which watches for your likeness online.

"Loti scans over 100M images and videos per day looking for abuse or breaches of your content or likeness."

"Loti provides DMCA takedowns when it finds content that's been shared without consent."

They also have a license management product called "Connect", and a "fake news protection" program called "Certify".

"Place an unobtrusive mark on your content to let your fans know it's really you."

"Let your fans verify your content by inspecting where it came from and who really sent it."

They don't say anything about how their technology works.

Hollywood celebs are scared of deepfakes. This talent agency will use AI to fight them.

#solidstatelife #ai #genai #computervision #deepfakes #aiethics

"Sonauto: Create hit songs with AI". Another AI music generator. I listened to Blue Scooby Doo ft. AI Beatles and Thanks Hacker News, done in the style of a country song. Pretty impressive. Give a listen. Check out the "Top of Week" and "Top of All Time" categories. I haven't had time to actually try creating a song, but if you do, let me know how it goes.

Sonauto: Create hit songs with AI

#solidstatelife #ai #genai #musicai

Udio generates AI-generated music. I went through the staff picks. I was impressed that it rendered "acoustic" music well with lyrics -- and the singing seemed actually good and the lyrics made sense. Does genres like jazz & country.

They don't say anything about how the system works. They say the program is free during the beta program.

Udio | Make your music

#solidstatelife #ai #genai #audioai #musicai

Why this developer is no longer using Copilot. He feels his programming skills atrophy. He writes code by pausing to wait for Copilot to write code, and doesn't enjoy programming that way. The AI-generated code is often wrong or out-of-date and has to be fixed. Using copilot is a privacy issue because your code is shared with Copilot.

I thought this was quite interesting. I tried Copilot in VSCode and I figured I wasn't using it much because I'm a vim user. So I tracked down the Neovim plug-in & got it working in vim, but still found I don't use it. Now I've come to feel it's great for certain use cases and bad for others. Where it's great is writing "boilerplate" code for using a public API. You just write a comment describing what you want to do and the beginning of the function, and Copilot spits out practically all the rest of the code for you function -- no tedious hours studying the documentation from the API provider.

But that's not the use case I actually engage in in real life. Most of what I do is either making a new UI, or porting code from PHP to Go. For the new UI, AI has been helpful -- I can take a screenshot, input it to ChatGPT, and ask it how to improve the AI. (I'm going to be trying this with Google's Gemini soon but I haven't tried it yet.) When it makes suggestions, I can ask it what HTML+CSS is needed to implement those suggestions. I've found it gets better and better for about 6 iterations. But you notice, Copilot isn't part of the loop. I'm jumping into dozens of files and making small changes, and that's a use case where Copilot just isn't helpful.

For porting code from PHP to Go, I modified a full-fledged PHP parser to transpile code to Go, and this has been critical because it's important that certain things, especially strings, get ported over exactly -- no room for errors. So this system parses PHP strings using PHP's parsing rules, and outputs Go strings using Go's parsing rules, and is always 100% right. Copilot isn't part of the loop and doesn't help.

Another place I've found AI incredibly useful is debugging problems where I have no clue what the problem might be. This goes back to using other people's large systems such as the public APIs mentioned earlier. Every now and then you get cryptic error messages or some other bizarre malfunction, and endless Google searching doesn't help. I can go to ChatGPT, Gemini, Claude, Perplexity, DeepSeek (and others, but those are the main ones I've been using) and say hey, I'm getting this cryptic error message or this weird behavior, and it can give you a nice list of things you might try. That can get you unstuck when you'd otherwise be very stuck.

It's kinda funny because, obviously I'm an avid follower of what's going on in AI, and happy to try AI tools, and I constantly run across other developers who say "Copilot has made me twice as productive!" or "Copilot has made me five times as productive!" or somesuch. I've wondered if there's something wrong with me because I haven't experienced those results at all. But AI has been helpful in other areas nobody ever seems to talk about.

Why I'm no longer using Copilot - Dreams of Code

#solidstatelife #ai #genai #llms #codingllms #openai #copilot

"Accessibility has failed: Try generative UI = individualized UX". Says legendary usability expert Jakob Nielsen. What he means by "accessibility" is borrowing the concept of "accessibility" in the physical world, where wheelchair ramps on buildings and busses are built, and so on, and applying it to the world of computing. This means, for example, making screen readers that translate screens into speech or braile, so blind or hearing-impared people can use computers. If you're a web developer you're supposed to fill in your "alt" attributes for all your image tags so screen readers can tell users what the image is. (Finishing out the headline, "UI" stands for "user interface" and "UX" stands for "user experience" -- most of you probably already know that.) Jakob Nielsen says:

"Accessibility has failed as a way to make computers usable for disabled users. My metrics for usable design are the same whether the user is disabled or not: whether it's easy to learn the system, whether productivity is high when performing tasks, and whether the design is pleasant -- even enjoyable -- to use."

"Assessed this way, the accessibility movement has been a miserable failure. Computers are still difficult, slow, and unpleasant for disabled users, despite about 30 years of trying. (I started promoting accessibility in 1996 when I worked at Sun Microsystems, but by no means claim to have been the first accessibility advocate.)"

"There are two reasons accessibility has failed:"

"Accessibility is too expensive for most companies to be able to afford everything that's needed with the current, clumsy implementation. There are too many different types of disabilities to consider for most companies to be able to conduct usability testing with representative customers with every kind of disability. Most companies either ignore accessibility altogether because they know that they won't be able to create a UX that's good enough to attract sufficient business from disabled customers, or they spend the minimum necessary to pass simplistic checklists but never run the usability studies with disabled users to confirm or reject the usability of the resulting design."

"Accessibility is doomed to create a substandard user experience, no matter how much a company invests, particularly for blind users who are given a linear (one-dimensional) auditory user interface to represent the two-dimensional graphical user interface (GUI) designed for most users."

"'Generative UI' is simply the application of artificial intelligence to automatically generate user interface design."

But he doesn't stop there. He goes on to envision "first-generation" and "second-generation" generative UI:

"'First-generation generative UI' for frozen designs where the AI only modifies the UI before shipping the product."

"I foresee a much more radical approach to generative UI to emerge shortly -- maybe in 5 years or so. In this second-generation generative UI, the user interface is generated afresh every time the user accesses the app. Most important, this means that different users will get drastically different designs. This is how we genuinely help disabled users."

Accessibility has failed: Try generative UI = individualized UX

#solidstatelife #hci #usability #ai #genai

"Agentic workflow" is what's next for AI, says Andrew Ng. Agentic meaning the AI acts as an "agent". Basically, ChatGPT gives you one-off answers. You ask it to write something for you, or write some code, and you can have follow-up conversation, but each time it has to generate a new response.

In the "agentic" workflow Andrew Ng envisions, the AI agent has a work item that it works on in an iterative manner, interacting with you at each step. If you ask a human programmer to write some code, they never blast out the whole thing right off the bat. They write some code and then iterate on it until they get it right. By changing language AIs into full-fledged agents, they will be able to engage in this practice themselves. An AI agent tasked with writing code can run and test its code, it can write its own unit tests, it can engage in self-reflection, and so on.

The next step after that is mult-agent collaboration. In this case you could give it a high level task, and an agent can do high-level planning, and other can search on HuggingFace for an AI model appropriate for the task, and another can write the code and so on.

What's next for AI agentic workflows ft. Andrew Ng of AI Fund - Sequoia Capital

#solidstatelife #ai #genai #llms #andrewng

3D AI Studio claims to create 3D models using AI. They say they can do text prompts and image input. The 3D models can be exported in many formats, including OBJ, STL, FBX, USD, and more.

Commercial product with free tier.

They don't say anything about how the system works.

3D AI Studio

#solidstatelife #ai #computervision #genai

"Will AI save physicians and clinicians time and from burnout?"

"Copilots for clinicians are also becoming more common. Ambient clinical documentation is a booming business. The technology allows doctors to record conversations with patients to automatically turn them into clinical notes and summaries using AI and is a major topic at Healthcare conferences like HIMSS conference this year, where more than 30,000 health and tech professionals gathered in Orlando, Florida."

"Earlier in March, Salesforce announced Einstein Copilot: Health Actions will allow doctors to book appointments, summarize patient information and send referrals by prompting AI with conversational language."

"Administrative workloads are a major problem for clinicians across the US health-care system. A survey published (via CNBC) by Athenahealth in February found that more than 90% of physicians report feeling burned out on a regular basis, largely because of the paperwork they are expected to complete."

"I used to be part of an admissions committee for a medical school. When I interviewed idealistic young people applying to medical school, 'typing' and 'filling out forms' was never once mentioned as a reason for becoming a physician."

She goes on to describe using AI for prior authorization letters that have to be written to insurance companies. These require a letter to be written to justify the use of a drug or therapy for a specific patient and to contain details of that specific patient and why that patient needs that therapy. These are frequently rejected by the insurance companies and have to be re-written over and over to eventually get approval. "A third of medical offices employ full-time staff to take care of the average 30 prior authorizations per physician per week."

On the flip side, "the insurers have started to use AI to deny claims more quickly."

Another use is referral letters from one physician to another. "Like prior authorization letters, these are pretty formulaic."

But the thing she has the most enthusiasm for is what she calls "ambient scribes". "Ambient scribes" are AI systems that listen in to the conversation between the patient and the physician and create a templated note for the medical record. "This technology allows physicians to avoid looking at a screen and typing while they're trying to connect with a patient."

"I've tried versions from multiple AI scribe companies (including TORTUS AI, which - full disclosure - I consult for) and they do an amazing job of filtering out irrelevant information and putting the information in the right spot."

"Think of the technological challenge inherent in this process: patient visits are often interrupted by clinic staff or phone calls, meander off into conversations about kids and dogs, and use abbreviations and technical jargon. They're often circular, meaning a patient will mention a symptom and the physician won't ask a follow up question about it until several minutes later. These tools produce a full transcript that uses generative AI to find the important information and put it into a form that's indistinguishable from what a physician would actually type. Many of my friends have reported that ambient scribes actually do a better job of including important details than they would have included themselves."

Will AI save physicians and clinicians time and from burnout?

#solidstatelife #ai #voicetotext #nlp #genai #llms #medicalai

The Scalable, Instructable, Multiworld Agent (SIMA) from DeepMind plays video games for you. You tell it what you want to do in regular language, and it goes into a 3D environment, including some provided by commercial video games, and carries out keyboard-and-mouse actions.

Before getting into how they did this, might be worth citing some of the reasons they thought this was challenging: Video games can be open-ended, visually complex, and have hundreds of different objects. Video games are asynchronous -- no turn taking like chess or Go, or many research environments, which stop and wait while the agent computes its next action. Each instance of a commercial video game needs its own GPU -- no running hundreds or thousands of actors per game per experiment as has been historically done in reinforcement learning. AI agents see the same screen pixels that a human player gets -- no access to internal game state, rewards, or any other "privileged information". AI agents use the same keyboard-and-mouse controls that humans do -- no handcrafted action spaces or high-level APIs.

In addition to all those challenges, they demanded their agents follow instructions in regular language, rather than simply pursuing a high score in the game, and the agents were not allowed to use simplified grammars or command sets.

"Since the agent-environment interface is human compatible, it allows agents the potential to achieve anything that a human could, and allows direct imitation learning from human behavior."

"A key motivation of SIMA is the idea that learning language and learning about environments are mutually reinforcing. A variety of studies have found that even when language is not necessary for solving a task, learning language can help agents to learn generalizable representations and abstractions, or to learn more efficiently." "Conversely, richly grounded learning can also support language learning."

I figure you're all eager to know what the games were. They were: Goat Simulator 3 (you play the goat), Hydroneer (you run a mining operation and dig for gold), No Man's Sky (you explore a galaxy of procedurally-generated planets), Satisfactory (you attempt to build a space elevator on an alien planet), Teardown (you complete heists by solving puzzles), Valheim (you try to survive in a world of Norse mythology), and Wobbly Life (you complete jobs to earn money to buy your own house).

However, before the games, they trained SIMA in research environments. Those, which you probably never heard of, are: Construction Lab (agents are challenged to build things from construction blocks), Playhouse (a procedurally-generated house), ProcTHOR (procedurally-generated rooms, such as offices and libraries), and WorldLab (an environment with better simulated physics).

The SIMA agent itself maps visual observations and language instructions to keyboard-and-mouse actions. But it does that in several stages. For input, it takes a language instruction from you, and the pixels of the screen.

The video and language instruction both go through encoding layers before being input to a single, large, multi-modal transformer. The transformer doesn't output keyboard and mouse actions directly. Instead, it outputs a "state representation" that gets fed into a reinforcement learning network, which translates the "state" into what in reinforcement learning parlance is called a "policy". A more intuitive regular word might be "strategy". Basically this is a function that, when given input from the environment including the agent's state within the environment, will output an action. Here, the actions are the same actions a human would take with mouse and keyboard.

The multi-modal transformer was trained from scratch. A recent new algorithm called Classifier-Free Guidance (CFG) was used, an algorithm inspired by the algorithms used by diffusion models to "condition" the diffusion model on the text you, the user, typed in.

Even in the research environments, it is hard to automate judging of whether an agent completed its tasks. Instructions may be such things as, "make a pile of rocks to mark this spot" or "see if you can jump over this chasm". The environment may not provide any signal indicating these have been fulfilled. There are some they can handle, though, like "move forward", "lift the green cube", and "use the knife to chop the carrots".

For commercial video games, all the agent gets is pixels on the screen, just like a human player, and has no access to the internal game state of the game. The games generally don't allow any game state to be saved and restored, something researchers like for reproducibility.

For video games, they resorted to detecting on-screen text using OCR. They did this in particular for two games, No Man's Sky and Valheim, "which both feature a significant amount of on-screen text."

Why not just have people look, i.e. have humans judge whether the instructions were followed? Turns out humans were "the slowest and most expensive." They were able to get judgments from humans who were experts at the particular game an agent was playing, though.

For automated judgment, if a task contains a knife, a cutting board, and a carrot, the agent may ascertain the goal ("cut the carrot on the cutting board") without relying on the language instruction. This example illustrates the need to differentiate between following a language task and inferring the language task from "environmental affordances".

How'd SIMA do? It looks like its success rate got up to about 60% for Playhouse, but only about 30% for Valheim. That's the percentage of tasks completed. The ranking goes Playhouse, Worldlab, Satisfactory, Construction Lab, No Man's Sky, Goat Simulator 3, and Valheim.

"Note that humans would also find some of these tasks challenging, and thus human-level performance would not be 100%."

Grouped by "skill category", movement instructions ("stop", "move", "look") were the easiest, while food and resource gathering instructions ("eat", "cook", "collect", "harvest") were the hardest.

For No Man's Sky, they did a direct comparison with humans. Human's averaged 60%, while SIMA had around 30%.

How long til the AIs can beat the humans?

A generalist AI agent for 3D virtual environments

#solidstatelife #ai #genai #llms #computervision #multimodal #videogames

Yesterday Google Chrome asked me if I want to try "out experimental AI features?"

(It lives at chrome://settings/ai -- you might see if it's available in yours. If not, it might be on the next update).

"These features use AI, are in early development, and won't always get it right."

I really don't want (even more of) my browser usage sent to Google's servers... but I can't resist, so I turned on the AI features to see what they do.

The features it advertises are:

"Help me write: Helps you write short-form content for things on the web, like reviews. Suggested content is based on your prompts and the content of the web page. To use this feature, right-click on a text box."

"Tab organizer: Automatically creates tab groups based on your open tabs. To use this feature, right-click on a tab and click Organize similar tabs."

To try out "Help me write", I punched in, "Today Google Chrome asks me if I want to try 'out experimental AI features?'".

After selecting "Elaborate" for "Length" and "Formal" for "Tone", I got:

"Today, Google Chrome prompted me to try out 'experimental AI features.' I clicked on the link and was directed to a page that described the features. The descriptions sounded interesting, but I am unsure what the features are or how they would improve my workflow. I am interested in learning whether anyone has tried these features and can share their evaluation of their usefulness."

I clicked on a button, not a link. Ha.

As for "Tab organizer", I clicked on a tab with a video about Boeing and clicked "Organize Similar Tabs".

It created a tab group called "Boeing Drama".

Here are the tabs it put together into the same tab group:

https://www.youtube.com/watch?v=Q8oCilY4szc - Boeing: Last Week Tonight with John Oliver (HBO)

https://www.youtube.com/watch?v=BlmYZ06F-78 - Boeing's killer plane - What went wrong? | ENDEVR Documentary

https://www.youtube.com/watch?v=NDEkH0zd3F8 - Scandal: Boeing's 737 Max disaster - Plainly Difficult

https://www.youtube.com/watch?v=UUuB0C1Nk8U - The SR-71 was much faster than the Air Force will admit - Sandboxx

https://www.youtube.com/watch?v=kLT1QEIIaB4 - Did beleaguered aircraft giant eliminate whistleblower? - Todd Grande

https://www.youtube.com/watch?v=dTmeswV3Ln0 - Boeing whistleblower found dead amid safety concerns and legal battle - dustin dailey

https://www.youtube.com/watch?v=Sdb44vY9VBw - "They Silenced Him." Boeing Whistleblower found dead after testifying | Attorney Ryan Explains

https://www.youtube.com/watch?v=OfoBxa7EoIo - The World with Yalda Hakim: Boeing whistleblower John Barnett found dead - Sky News

https://www.youtube.com/watch?v=mwAtCavQQlA - "Dead after testifying" - Was Boeing whistle blower John Barnett killed to silence him? - Valuetainment

https://www.youtube.com/watch?v=eOffvIaWNm4 - Ex-Boeing Quality Manager Warns of 737 Plane Being Back Air So Soon | TMZ Live - Jan 31, 2024

https://news.ycombinator.com/item?id=39673589 - Boeing whistleblower found dead in US (bbc.com)

https://news.ycombinator.com/item?id=39673589 - Boeing whistleblower found dead in US (bbc.com)

It included the Hacker News link twice. But I had it open twice so maybe it should have done that?

And if you look closely, you'll notice it snuck in one video that's not about Boeing. There's an SR-71 video in there. It kind of makes sense that it's in the group because it's also about aviation, but the label it came up with for the tab group wasn't "Aviation", it was "Boeing Drama". So, there's a little bit of disconnect between the clustering algorithm and the labelling algorithm.

Also, and if you're thinking most of the tabs open on my machine were about Boeing, you'd be wrong. I've got 320 tabs open. So, 13 about Boeing, 307 about other topics. As a percentage, 4% about Boeing. (More on that below.)

And yes, I know you all count on me to bring you insights into the latest AI developments (lol), but I got sucked into the "Boeing news" rabbit hole. (More on that below, too).

[Experimental AI](chrome://settings/ai)

#solidstatelife #ai #genai #llms #googlechrome

"Ema, a 'Universal AI employee,' emerges from stealth with $25M."

"Meet Ema, a universal AI employee that boosts productivity across every role in your organization. She is simple to use, trusted, and accurate."

[Insert joke here about how saying things like that won't make people worry about their jobs.]

"Ema's the missing operating system that makes Generative AI work at an enterprise level. Using proprietary Generative Workflow Engine, Ema automates complex workflows with a simple conversation. She is trusted, compliant and keeps your data safe. EmaFusion model combines the outputs from the best models (public large language models and custom private models) to amplify productivity with unrivaled accuracy. See how Ema can transform your business today."

"They say Ema (the company) has already quietly amassed customers while still in stealth, including Envoy Global, TrueLayer, and Moneyview."

"Ema's Personas operate on our patent-pending Generative Workflow Engine (GWE), which goes beyond simple language prediction to dynamically map out workflows with a simple conversation. Our platform offers Standard Personas for common enterprise roles such as Customer Service Specialists (CX), Employee Assistant (EX), Data Analyst, Sales Assistant etc. and allows for the rapid creation of Specialized Personas tailored to rapidly automate unique workflows. No more waiting for months to build Gen AI apps that work!"

"To address accuracy issues and computational costs inherent in current Gen AI applications, Ema leverages our proprietary "fusion of experts" model, EmaFusion, that exceeds 2 Trillion parameters. EmaFusion intelligently combines many large language models (over 30 today and that number keeps growing), such as Claude, Gemini, Mistral, Llama2, GPT4, GPT3.5, and Ema's own custom models. Furthermore, EmaFusion supports integration of customer developed private models, maximizing accuracy at the most optimal cost for every task."

Oh, and "Ema" stands for "enterprise machine assistant".

Ema "taps into more than 30 large language models."

"As for what Ema can do, these businesses are using it in applications that range from customer service -- including offering technical support to users as well as tracking and other functions -- through to internal productivity applications for employees. Ema's two products -- Generative Workflow Engine (GWE) and EmaFusion -- are designed to "emulate human responses" but also evolve with more usage with feedback."

They also say, "Pre-integrated with hundreds of apps, Ema is easy to configure and deploy."

What are those integrations? They said some of those integrations are: Box, Dropbox, Google Drive, OneDrive, SharePoint, Clear Books, FreeAgent, FreshBooks, Microsoft Dynamics 365, Moneybird, NetSuite, QuickBooks Online, Sage Business Cloud, Sage Intacct, Wave Financial, Workday, Xero, Zoho Books, Aha!, Asana, Azure DevOps, Basecamp, Bitbucket, ClickUp, Dixa, Freshdesk, Freshservice, Front, GitHub Issues, GitLab, Gladly, Gorgias, Height, Help Scout, Hive, Hubspot Ticketing, Intercom, Ironclad, Jira, Jira Service Management, Kustomer, Linear, Pivotal Tracker, Rally, Re:amaze, Salesforce Service Cloud, ServiceNow, Shortcut, SpotDraft, Teamwork, Trello, Wrike, Zendesk, Zoho BugTracker, Zoho Desk, Accelo, ActiveCampaign, Affinity, Capsule, Close, Copper, HubSpot, Insightly, Keap, Microsoft Dynamics 365 Sales, Nutshell, Pipedrive, Pipeliner, Salesflare, Salesforce, SugarCRM, Teamleader, Teamwork CRM, Vtiger, Zendesk Sell, Zoho CRM, ApplicantStack, Ashby, BambooHR, Breezy, Bullhorn, CATS, ClayHR, Clockwork, Comeet, Cornerstone TalentLink, EngageATS, Eploy, Fountain, Freshteam, Greenhouse, Greenhouse - Job Boards API, Harbour ATS, Homerun, HR Cloud, iCIMS, Infinite BrassRing, JazzHR, JobAdder, JobScore, Jobsoid, Jobvite, Lano, Lever, Oracle Fusion - Recruiting Cloud, Oracle Taleo, Personio Recruiting, Polymer, Recruitee, Recruiterflow, Recruitive, Sage HR, SAP SuccessFactors, SmartRecruiters, TalentLyft, TalentReef, Teamtailor, UKG Pro Recruiting, Workable, Workday, Zoho Recruit, ActiveCampaign, Customer.io, getResponse, Hubspot Marketing Hub, Keap, Klaviyo, Mailchimp, MessageBird, Podium, SendGrid, Sendinblue, 7Shifts, ADP Workforce Now, AlexisHR, Altera Payroll, Azure Active Directory, BambooHR, Breathe, Ceridian Dayforce, Charlie, ChartHop, ClayHR, Deel, Factorial, Freshteam, Google Workspace, Gusto, Hibob, HRAlliance, HR Cloud, HR Partner, Humaans, Insperity Premier, IntelliHR, JumpCloud, Justworks, Keka, Lano, Lucca, Namely, Nmbrs, Officient, Okta, OneLogin, OysterHR, PayCaptain, Paychex, Paycor, PayFit, Paylocity, PeopleHR, Personio, PingOne, Proliant, Rippling, Sage HR, Sapling, SAP SuccessFactors, Sesame, Square Payroll, TriNet, UKG Dimensions, UKG Pro, UKG Ready, Workday, and Zenefits.

Ema, a 'Universal AI employee,' emerges from stealth with $25M

#solidstatelife #ai #genai #llms #aiagents #technologicalunemployment

Devon "the first AI software engineer"

You put it in the "driver's seat" and it does everything for you. Or at least that's the idea.

"Benchmark the performance of LLaMa".

Devon builds the whole project, uses the browser to pull up API documentation, runs into an unexpected error, adds a debugging print statement, uses the error in the logs to figure out how to fix the bug, then builds and deploys a website with full styling as visualization.

See below for reactions.

Introducing Devin, the first AI software engineer - Cognition

#solidstatelife #ai #genai #llms #codingai #technologicalunemployment

"AI mishaps are surging -- and now they're being tracked like software bugs".

The article is about a new "AI Incident Database", modeled after the Common Vulnerabilities and Exposures (CVE) database run by MITRE and the National Highway Transport Safety Administration's database of vehicle crashes.

I clicked through to the site and here are some examples of what I found:

"Self-Driving Waymo Collides With Bicyclist In Potrero Hill" -- sfist.com - 2024

"Waymo robotaxi accident with San Francisco cyclist draws regulatory review" - reuters.com - 2024

"AI images of Donald Trump with black voters spread before election" - thetimes.co.uk - 2024

"Google AI's answer on whether Modi is 'fascist' sparks outrage in India, calls for tough laws" - scmp.com - 2024

"The AI Culture Wars Are Just Getting Started" - wired.com - 2024

"Gemini image generation got it wrong. We'll do better." - blog.google - 2024

"Google's hidden AI diversity prompts lead to outcry over historically inaccurate images" - arstechnica.com - 2024

"Google suspends Gemini AI chatbot's ability to generate pictures of people" - apnews.com - 2024

"ChatGPT has gone mad today, OpenAI says it is investigating reports of unexpected responses" - indiatoday.in - 2024

"Fake sexually explicit video of podcast host Bobbi Althoff trends on X despite violating platform's rules" - nbcnews.com - 2024

"Bobbi Althoff Breaks Her Silence On Deepfake Masturbation Video" - dailycaller.com - 2024

"North Korea and Iran using AI for hacking, Microsoft says" - theguardian.com - 2024

"ChatGPT Used by North Korean Hackers to Scam LinkedIn Users" - tech.co - 2024

"Analysis reveals high probability of Starmer's audio on Rochdale to be a deepfake" - logicallyfacts.com - 2024

"Happy Valentine's Day! Romantic AI Chatbots Don't Have Your Privacy at Heart" - foundation.mozilla.org - 2024

"Your AI Girlfriend Is a Data-Harvesting Horror Show" - gizmodo.com - 2024

"No, France 24 did not report that Kyiv planned to 'assassinate' French President" - logicallyfacts.com - 2024

"Les Observateurs - Un projet d'assassinat contre Emmanuel Macron en Ukraine ? Attention, cette vidéo est truquée" - observers.france24.com - 2024

"Deepfakes, Internet Access Cuts Make Election Coverage Hard, Journalists Say" - voanews.com - 2024

"Imran Khan's PTI to boycott polls? Deepfake audio attempts to mislead voters in Pakistan" - logicallyfacts.com - 2024

"Finance worker pays out $25 million after video call with deepfake 'chief financial officer'" - cnn.com - 2024

"Fake news YouTube creators target Black celebrities with AI-generated misinformation" - nbcnews.com - 2024

"Australian news network apologises for 'graphic error' after photo of MP made more revealing" - news.sky.com - 2024

"Australian News Channel Apologises To MP For Editing Body, Outfit In Pic" - ndtv.com - 2024

"Adobe confirms edited image of Georgie Purcell would have required 'human intervention'" - womensagenda.com.au - 2024

"Nine slammed for 'AI editing' a Victorian MP's dress" - lsj.com.au - 2024

"An AI-generated image of a Victorian MP raises wider questions on digital ethics" - abc.net.au - 2024

AI mishaps are surging -- and now they're being tracked like software bugs - The Register

#solidstatelife #ai #aiethics #genai #deepfakes