#AI In Production Line Optimization

[rubylogan15]

Learn how generative AI addresses key manufacturing challenges with predictive maintenance, advanced design optimization, superior quality control, and seamless supply chains.

[nostalgebraist]

Honestly I'm pretty tired of supporting nostalgebraist-autoresponder. Going to wind down the project some time before the end of this year.

Posting this mainly to get the idea out there, I guess.

This project has taken an immense amount of effort from me over the years, and still does, even when it's just in maintenance mode.

Today some mysterious system update (or something) made the model no longer fit on the GPU I normally use for it, despite all the same code and settings on my end.

This exact kind of thing happened once before this year, and I eventually figured it out, but I haven't figured this one out yet. This problem consumed several hours of what was meant to be a relaxing Sunday. Based on past experience, getting to the bottom of the issue would take many more hours.

My options in the short term are to

A. spend (even) more money per unit time, by renting a more powerful GPU to do the same damn thing I know the less powerful one can do (it was doing it this morning!), or

B. silently reduce the context window length by a large amount (and thus the "smartness" of the output, to some degree) to allow the model to fit on the old GPU.

Things like this happen all the time, behind the scenes.

I don't want to be doing this for another year, much less several years. I don't want to be doing it at all.

----

In 2019 and 2020, it was fun to make a GPT-2 autoresponder bot.

[EDIT: I've seen several people misread the previous line and infer that nostalgebraist-autoresponder is still using GPT-2. She isn't, and hasn't been for a long time. Her latest model is a finetuned LLaMA-13B.]

Hardly anyone else was doing anything like it. I wasn't the most qualified person in the world to do it, and I didn't do the best possible job, but who cares? I learned a lot, and the really competent tech bros of 2019 were off doing something else.

And it was fun to watch the bot "pretend to be me" while interacting (mostly) with my actual group of tumblr mutuals.

In 2023, everyone and their grandmother is making some kind of "gen AI" app. They are helped along by a dizzying array of tools, cranked out by hyper-competent tech bros with apparently infinite reserves of free time.

There are so many of these tools and demos. Every week it seems like there are a hundred more; it feels like every day I wake up and am expected to be familiar with a hundred more vaguely nostalgebraist-autoresponder-shaped things.

And every one of them is vastly better-engineered than my own hacky efforts. They build on each other, and reap the accelerating returns.

I've tended to do everything first, ahead of the curve, in my own way. This is what I like doing. Going out into unexplored wilderness, not really knowing what I'm doing, without any maps.

Later, hundreds of others with go to the same place. They'll make maps, and share them. They'll go there again and again, learning to make the expeditions systematically. They'll make an optimized industrial process of it. Meanwhile, I'll be locked in to my own cottage-industry mode of production.

Being the first to do something means you end up eventually being the worst.

----

I had a GPT chatbot in 2019, before GPT-3 existed. I don't think Huggingface Transformers existed, either. I used the primitive tools that were available at the time, and built on them in my own way. These days, it is almost trivial to do the things I did, much better, with standardized tools.

I had a denoising diffusion image generator in 2021, before DALLE-2 or Stable Diffusion or Huggingface Diffusers. I used the primitive tools that were available at the time, and built on them in my own way. These days, it is almost trivial to do the things I did, much better, with standardized tools.

Earlier this year, I was (probably) one the first people to finetune LLaMA. I manually strapped LoRA and 8-bit quantization onto the original codebase, figuring out everything the hard way. It was fun.

Just a few months later, and your grandmother is probably running LLaMA on her toaster as we speak. My homegrown methods look hopelessly antiquated. I think everyone's doing 4-bit quantization now?

(Are they? I can't keep track anymore -- the hyper-competent tech bros are too damn fast. A few months from now the thing will be probably be quantized to -1 bits, somehow. It'll be running in your phone's browser. And it'll be using RLHF, except no, it'll be using some successor to RLHF that everyone's hyping up at the time...)

"You have a GPT chatbot?" someone will ask me. "I assume you're using AutoLangGPTLayerPrompt?"

No, no, I'm not. I'm trying to debug obscure CUDA issues on a Sunday so my bot can carry on talking to a thousand strangers, every one of whom is asking it something like "PENIS PENIS PENIS."

Only I am capable of unplugging the blockage and giving the "PENIS PENIS PENIS" askers the responses they crave. ("Which is ... what, exactly?", one might justly wonder.) No one else would fully understand the nature of the bug. It is special to my own bizarre, antiquated, homegrown system.

I must have one of the longest-running GPT chatbots in existence, by now. Possibly the longest-running one?

I like doing new things. I like hacking through uncharted wilderness. The world of GPT chatbots has long since ceased to provide this kind of value to me.

I want to cede this ground to the LLaMA techbros and the prompt engineers. It is not my wilderness anymore.

I miss wilderness. Maybe I will find a new patch of it, in some new place, that no one cares about yet.

----

Even in 2023, there isn't really anything else out there quite like Frank. But there could be.

If you want to develop some sort of Frank-like thing, there has never been a better time than now. Everyone and their grandmother is doing it.

"But -- but how, exactly?"

Don't ask me. I don't know. This isn't my area anymore.

There has never been a better time to make a GPT chatbot -- for everyone except me, that is.

Ask the techbros, the prompt engineers, the grandmas running OpenChatGPT on their ironing boards. They are doing what I did, faster and easier and better, in their sleep. Ask them.

[txttletale]

I think the reason I dislike AI generative software (I'm fine with AI analysis tools, like for example splitting audio into tracks) is that I am against algorithmically generated content. I don't like the internet as a pit of content slop. AI art isn't unique in that regard, and humans can make algorithmically generated content too (look at youtube for example). AI makes it way easier to churn out content slop and makes searching for non-slop content more difficult.

yeah i basically wholeheartedly agree with this. you are absolutely right to point out that this is a problem that far predates AI but has been exacerbated by the ability to industrialise production. Content Slop is absolutely one of the first things i think of when i use that "if you lose your job to AI, it means it was already automated" line -- the job of a listicle writer was basically to be a middleman between an SEO optimization tool and the Google Search algorithm. the production of that kind of thing was already being made by a computer for a computer, AI just makes it much faster and cheaper because you don't have to pay a monkey to communicate between the two machines. & ai has absolutely made this shit way more unbearable but ultimately y'know the problem is capitalism incentivising the creation of slop with no purpose other than to show up in search results

[probablyasocialecologist]

Google search really has been taken over by low-quality SEO spam, according to a new, year-long study by German researchers. The researchers, from Leipzig University, Bauhaus-University Weimar, and the Center for Scalable Data Analytics and Artificial Intelligence, set out to answer the question "Is Google Getting Worse?" by studying search results for 7,392 product-review terms across Google, Bing, and DuckDuckGo over the course of a year.  They found that, overall, "higher-ranked pages are on average more optimized, more monetized with affiliate marketing, and they show signs of lower text quality ...  we find that only a small portion of product reviews on the web uses affiliate marketing, but the majority of all search results do."  They also found that spam sites are in a constant war with Google over the rankings, and that spam sites will regularly find ways to game the system, rise to the top of Google's rankings, and then will be knocked down. "SEO is a constant battle and we see repeated patterns of review spam entering and leaving the results as search engines and SEO engineers take turns adjusting their parameters," they wrote.

[...]

The researchers warn that this rankings war is likely to get much worse with the advent of AI-generated spam, and that it genuinely threatens the future utility of search engines: "the line between benign content and spam in the form of content and link farms becomes increasingly blurry—a situation that will surely worsen in the wake of generative AI. We conclude that dynamic adversarial spam in the form of low-quality, mass-produced commercial content deserves more attention."

[elkement]

Frozen Harmonics - Print Test

Got my haul from my local printshop yesterday :-) I had my mathematical artwork "Frozen Harmonics" printed on canvas - and I absolutely like the result!

My "product photography" has room for improvement, but the colors and the black background really look way more vibrant / saturated than I expected. The black looks perhaps even "blacker" than on my metal prints. I also like how the canvas wraps around the frame, but I need to take that into account for future creations. This image was one of the few of my math / code artworks that had enough "margin suitable for wrapping".

Photos taken in natural indoor light about 1-2 meters from a window, but not in direct sunlight. I should perhaps edit the photo for color correction (or make an effort to take better photos :-)), but I just wanted to share it "as is"!

Digital original:

Digital art created with custom JavaScript code using the framework three.js. No AI involved. Contour lines on nested surfaces of spherical harmonic functions (the building blocks of orbitals in quantum mechanics - but this is a crazy combinations of such functions.)

Size of the print: 30cm x 30cm | 12in x 12in Image: 5000x5000 pixels

I figured the structure of the canvas would interfere with these lines in a non-optimal way, but I feel it looks smooth and adds a bit of interesting texture - just as the roughness of matt metal prints does.

Canvas print on INPRNT (shipping from the US) - my test was from a local "consumer-grade" printshop, so I am pretty sure that INPRNT's canvas prints are even better:

[punk-pins]

fundamentally you need to understand that the internet-scraping text generative AI (like ChatGPT) is not the point of the AI tech boom. the only way people are making money off that is through making nonsense articles that have great search engine optimization. essentially they make a webpage that’s worded perfectly to show up as the top result on google, which generates clicks, which generates ads. text generative ai is basically a machine that creates a host page for ad space right now.

and yeah, that sucks. but I don’t think the commercialized internet is ever going away, so here we are. tbh, I think finding information on the internet, in books, or through anything is a skill that requires critical thinking and cross checking your sources. people printed bullshit in books before the internet was ever invented. misinformation is never going away. I don’t think text generative AI is going to really change the landscape that much on misinformation because people are becoming educated about it. the text generative AI isn’t a genius supercomputer, but rather a time-saving tool to get a head start on identifying key points of information to further research.

anyway. the point of the AI tech boom is leveraging big data to improve customer relationship management (CRM) to streamline manufacturing. businesses collect a ridiculous amount of data from your internet browsing and purchases, but much of that data is stored in different places with different access points. where you make money with AI isn’t in the Wild West internet, it’s in a structured environment where you know the data its scraping is accurate. companies like nvidia are getting huge because along with the new computer chips, they sell a customizable ecosystem along with it.

so let’s say you spent 10 minutes browsing a clothing retailer’s website. you navigated directly to the clothing > pants tab and filtered for black pants only. you added one pair of pants to your cart, and then spent your last minute or two browsing some shirts. you check out with just the pants, spending $40. you select standard shipping.

with AI for CRM, that company can SIGNIFICANTLY more easily analyze information about that sale. maybe the website developers see the time you spent on the site, but only the warehouse knows your shipping preferences, and sales audit knows the amount you spent, but they can’t see what color pants you bought. whereas a person would have to connect a HUGE amount of data to compile EVERY customer’s preferences across all of these things, AI can do it easily.

this allows the company to make better broad decisions, like what clothing lines to renew, in which colors, and in what quantities. but it ALSO allows them to better customize their advertising directly to you. through your browsing, they can use AI to fill a pre-made template with products you specifically may be interested in, and email it directly to you. the money is in cutting waste through better manufacturing decisions, CRM on an individual and large advertising scale, and reducing the need for human labor to collect all this information manually.

(also, AI is great for developing new computer code. where a developer would have to trawl for hours on GitHUB to find some sample code to mess with to try to solve a problem, the AI can spit out 10 possible solutions to play around with. thats big, but not the point right now.)

so I think it’s concerning how many people are sooo focused on ChatGPT as the face of AI when it’s the least profitable thing out there rn. there is money in the CRM and the manufacturing and reduced labor. corporations WILL develop the technology for those profits. frankly I think the bigger concern is how AI will affect big data in a government ecosystem. internet surveillance is real in the sense that everything you do on the internet is stored in little bits of information across a million different places. AI will significantly impact the government’s ability to scrape and compile information across the internet without having to slog through mountains of junk data.

[hypocrite-human]

AI & IT'S IMPACT

Unleashing the Power: The Impact of AI Across Industries and Future Frontiers

Artificial Intelligence (AI), once confined to the realm of science fiction, has rapidly become a transformative force across diverse industries. Its influence is reshaping the landscape of how businesses operate, innovate, and interact with their stakeholders. As we navigate the current impact of AI and peer into the future, it's evident that the capabilities of this technology are poised to reach unprecedented heights.

1. Healthcare:

In the healthcare sector, AI is a game-changer, revolutionizing diagnostics, treatment plans, and patient care. Machine learning algorithms analyze vast datasets to identify patterns, aiding in early disease detection. AI-driven robotic surgery is enhancing precision, reducing recovery times, and minimizing risks. Personalized medicine, powered by AI, tailors treatments based on an individual's genetic makeup, optimizing therapeutic outcomes.

2. Finance:

AI is reshaping the financial industry by enhancing efficiency, risk management, and customer experiences. Algorithms analyze market trends, enabling quicker and more accurate investment decisions. Chatbots and virtual assistants powered by AI streamline customer interactions, providing real-time assistance. Fraud detection algorithms work tirelessly to identify suspicious activities, bolstering security measures in online transactions.

3. Manufacturing:

In manufacturing, AI is optimizing production processes through predictive maintenance and quality control. Smart factories leverage AI to monitor equipment health, reducing downtime by predicting potential failures. Robots and autonomous systems, guided by AI, enhance precision and efficiency in tasks ranging from assembly lines to logistics. This not only increases productivity but also contributes to safer working environments.

4. Education:

AI is reshaping the educational landscape by personalizing learning experiences. Adaptive learning platforms use AI algorithms to tailor educational content to individual student needs, fostering better comprehension and engagement. AI-driven tools also assist educators in grading, administrative tasks, and provide insights into student performance, allowing for more effective teaching strategies.

5. Retail:

In the retail sector, AI is transforming customer experiences through personalized recommendations and efficient supply chain management. Recommendation engines analyze customer preferences, providing targeted product suggestions. AI-powered chatbots handle customer queries, offering real-time assistance. Inventory management is optimized through predictive analytics, reducing waste and ensuring products are readily available.

6. Future Frontiers:

A. Autonomous Vehicles: The future of transportation lies in AI-driven autonomous vehicles. From self-driving cars to automated drones, AI algorithms navigate and respond to dynamic environments, ensuring safer and more efficient transportation. This technology holds the promise of reducing accidents, alleviating traffic congestion, and redefining mobility.

B. Quantum Computing: As AI algorithms become more complex, the need for advanced computing capabilities grows. Quantucm omputing, with its ability to process vast amounts of data at unprecedented speeds, holds the potential to revolutionize AI. This synergy could unlock new possibilities in solving complex problems, ranging from drug discovery to climate modeling.

C. AI in Creativity: AI is not limited to data-driven tasks; it's also making inroads into the realm of creativity. AI-generated art, music, and content are gaining recognition. Future developments may see AI collaborating with human creators, pushing the boundaries of what is possible in fields traditionally associated with human ingenuity.

In conclusion, the impact of AI across industries is profound and multifaceted. From enhancing efficiency and precision to revolutionizing how we approach complex challenges, AI is at the forefront of innovation. The future capabilities of AI hold the promise of even greater advancements, ushering in an era where the boundaries of what is achievable continue to expand. As businesses and industries continue to embrace and adapt to these transformative technologies, the synergy between human intelligence and artificial intelligence will undoubtedly shape a future defined by unprecedented possibilities.

[drdemonprince]

Do you think that advances in AI technology will be better or worse for the culture of productivity? 

On the one hand, offloading time-consuming automation tasks to AI could allow for the same amount of work to get done in a shorter time, and could pave the way for a shorter work week. On the other hand, companies could just raise expectations that more work gets done per week, assuming that AI is allowing human workers to get more done in a shorter amount of time. Or companies could lay off more human staff, leaving less humans to do the same amount of work assuming they are relying on AI to get more done.

it's gonna be about as bad for humanity as any other leap forward in industrial technology. people didn't exactly start working less after the invention of the steam engine or the cotton gin or the electric motor or assembly line or the computer. though these technologies and processes meant an individual laborer could accomplish more work than ever before, it was the people who owned the means of production who skimmed off the profits and enjoyed extra leisure. technological gains are nothing but new ways to extract additional labor out of humans until our every conscious & unconscious moment is devoted to optimization. unless we come together to demand otherwise and to claim control over these tools.

[nunuslab24]

What are AI, AGI, and ASI? And the positive impact of AI

Understanding artificial intelligence (AI) involves more than just recognizing lines of code or scripts; it encompasses developing algorithms and models capable of learning from data and making predictions or decisions based on what they’ve learned. To truly grasp the distinctions between the different types of AI, we must look at their capabilities and potential impact on society.

To simplify, we can categorize these types of AI by assigning a power level from 1 to 3, with 1 being the least powerful and 3 being the most powerful. Let’s explore these categories:

1. Artificial Narrow Intelligence (ANI)

Also known as Narrow AI or Weak AI, ANI is the most common form of AI we encounter today. It is designed to perform a specific task or a narrow range of tasks. Examples include virtual assistants like Siri and Alexa, recommendation systems on Netflix, and image recognition software. ANI operates under a limited set of constraints and can’t perform tasks outside its specific domain. Despite its limitations, ANI has proven to be incredibly useful in automating repetitive tasks, providing insights through data analysis, and enhancing user experiences across various applications.

2. Artificial General Intelligence (AGI)

Referred to as Strong AI, AGI represents the next level of AI development. Unlike ANI, AGI can understand, learn, and apply knowledge across a wide range of tasks, similar to human intelligence. It can reason, plan, solve problems, think abstractly, and learn from experiences. While AGI remains a theoretical concept as of now, achieving it would mean creating machines capable of performing any intellectual task that a human can. This breakthrough could revolutionize numerous fields, including healthcare, education, and science, by providing more adaptive and comprehensive solutions.

3. Artificial Super Intelligence (ASI)

ASI surpasses human intelligence and capabilities in all aspects. It represents a level of intelligence far beyond our current understanding, where machines could outthink, outperform, and outmaneuver humans. ASI could lead to unprecedented advancements in technology and society. However, it also raises significant ethical and safety concerns. Ensuring ASI is developed and used responsibly is crucial to preventing unintended consequences that could arise from such a powerful form of intelligence.

The Positive Impact of AI

When regulated and guided by ethical principles, AI has the potential to benefit humanity significantly. Here are a few ways AI can help us become better:

• Healthcare: AI can assist in diagnosing diseases, personalizing treatment plans, and even predicting health issues before they become severe. This can lead to improved patient outcomes and more efficient healthcare systems.

• Education: Personalized learning experiences powered by AI can cater to individual student needs, helping them learn at their own pace and in ways that suit their unique styles.

• Environment: AI can play a crucial role in monitoring and managing environmental changes, optimizing energy use, and developing sustainable practices to combat climate change.

• Economy: AI can drive innovation, create new industries, and enhance productivity by automating mundane tasks and providing data-driven insights for better decision-making.

In conclusion, while AI, AGI, and ASI represent different levels of technological advancement, their potential to transform our world is immense. By understanding their distinctions and ensuring proper regulation, we can harness the power of AI to create a brighter future for all.

[lobautumny]

This toy's been thinking off and on about AI a lot over the last few months, and it's been mulling over a lot of arguments from both sides, and there's been something gnawing at the back of its mind: It detests the concept of AI media generation, yet it finds most common anti-AI talking points to be very ineffective. And this causes the question to keep coming up in its mind of whether it's the incorrect one, if AI art really is creatively valid, if this is simply the future of art. But then, just now, it suddenly had a realization.

Of fucking course AI is not the future of art, and it's not for any deep philosophical reason about the fundamental nature of art or creativity or any of that shit. It comes down to one simple fact: Passionate artists create for the joy of the process of creation, to put themselves into their work and lovingly craft every detail. Sure, you could use AI to massively increase your output, but if you genuinely have a love for creating art, then no matter how good the quality of the AI-generated results get, that's not going to matter to you. No matter what, until the last person draws their last breath, those who genuinely have a desire to create art are going to want to make it themselves, not automate it with a machine. And that's how it is with any hobby.

For a point of comparison, saying that AI is the future of art would be like saying that AI is the future of video games and that nobody is actually going to be playing video games themselves anymore in a few years because they can just get a machine to do it better than they could. Like, even if such a machine existed, there would be no shortage of people who actually want to play the video games themselves, because their passion lies in, y'know, actually performing the gameplay.

This has also led this toy to the realization that the fundamental reason it hates the concept of AI-generated media so much, and the notion that it is the future of artistic expression, is that these ideas hinge on a perception of art that only people who hate making art could have. Anyone who delivers these kinds of lines wants to be seen as a serious artist, but believes that all there is to art is results. They see it, consciously or not, as a consumer product, something that exists to generate capital from a market audience. This is the only framework through which optimizing the process of creating art out of art makes any amount of sense. And it happens to be the same mentality that leads to the tragedy of artists giving up a couple months in because they've bought into any number of lies about simply not having talent, or their art not being worth anything because it isn't abstractly "good" enough. The thought process behind the AI artist is part of that depressive spiral of loathing.

This is why AI, as a cultural/artistic movement, is bound to fail. The technology is still new and extremely novel and improving a lot and there's a ton of conversations going on about it and what it means for the future and its political ramifications, and that means that it's this big cultural event right now, but what happens when the dust settles? What happens when the technology is no longer novel, and it's improving slowly? What happens when the big conversations about it outside of dedicated AI communities slow down? What happens in 5 years when we see flop after flop after flop from big companies trying to cash in on the AI craze by making movies written entirely by AI, albums composed entirely by AI, games programmed entirely by AI? What happens when courts eventually rule that you're not allowed to train an AI on (or use an AI trained on) copyrighted works without the copyright-holder's express permission? This toy doesn't believe this is all actually leading up to anything grand. As far as it can tell, it looks like the hype is going to fizzle out past a certain point, the movement behind it will die, and AI will remain primarily as a niche tool for artists to use in their otherwise-manual process, a way to shitpost, and a way to quickly process bulk data.

[maximumwobblerbanditdonut]

The Strike Is Over! SAG-AFTRA & Studios Reach Deal On New Three-Year Contract

Dominic Patten And Anthony D'Alessandro

November 8, 2023 4:39PM PST

After 118 days of the actors guild being out on strike, SAG-AFTRA and the studios have reached a tentative deal on a new contract that could see Hollywood up and running again within weeks.

The strike will be over as of 12:01 am PT November 9, we hear. Culminating a very dramatic day of studio earnings results and deadlines, the actors guild’s 17-member negotiating committee unanimously voted to recommend a tentative agreement to the SAG-AFTRA board.

Coming just less than a month after Writers Guild members overwhelmingly ratified their own agreement with the Alliance of Motion Picture and Television Producers, SAG-AFTRA’s deal is the culmination of the latest round of renewed negotiations that began October 24. Indicating the seriousness and stakes of the negotiations, Netflix’s Ted Sarandos, Disney’s Bob Iger, NBCUniversal’s Donna Langley and Warner Bros Discovery’s David Zaslav frequently directly participated in the talks.

The tentative agreement follows the studios responding on November 3 to the guild’s last comprehensive counter with a self-described “historic” package. That was succeeded less than 24 hours later by an expanded group of studio leaders — including execs from Paramount, Amazon, Apple and more — joining the Gang of Four to brief SAG-AFTRA on the AMPTP’s new offer, which was said to include big gains in wages and bonuses as well as sweeping AI protections.

We didn’t just come toward you, we came all the way to you,” Sarandos told guild leaders Saturday before SAG-AFTRA brass began digging into the fine print. Further talks between the two sides began earlier this week as the guild poured over the studios’ latest set of proposals.

Now, if all goes as planned and the board signs off on the deal, eligible members of the 160,000-strong actors guild will vote soon to ratify the new agreement. Also, with SAG-AFTRA pulling the plug on the strike just after midnight and before the ratification vote is completed, people could be back to work soon and production restarted quickly.

Exposing many of the shifts and divisions in the industry over the past decade, today’s tentative agreement comes at the end of a long road filled with diversions and potholes.

Overall, the six months of Hollywood strikes is estimated to have cost the Southern California economy more than $6.5 billion and 45,000 entertainment industry jobs after production ground to a halt with the WGA hitting the picket lines in early May and SAG-AFTRA following in mid-July. On an individual level, the labor action garnered passionate unity among guild members. At the same time, a fact not lost on the studios and their strategy, many guild members have suffered crippling financial hardship, as have below-the-line workers, going months without work.

After calling the strike July 14, it took the guild and the studio CEOs’ Gang of Four around 80 days before their first official face-to-face talks at SAG-AFTRA headquarters on Wilshire Boulevard. For all the optimism and momentum coming out of the completed WGA deal, those new deliberations between SAG-AFTRA and the studios that began October 2 blew apart on October 11, with the AMPTP leaving negotiations early after the guild tabled an alternative to its contentious revenue-sharing proposal. A few hours later, expecting more scheduled talks the next day, SAG-AFTRA president Fran Drescher and chief negotiator Duncan Crabtree-Ireland received a call saying deliberations were “suspended.”

“Last night, they introduced a levy on subscribers on top of [other] areas,” Sarandos said the next day at an industry conference, calling the proposal a “bridge too far” and blaming the guild for the talks ending. Later, SAG-AFTRA accused the studios of “bully tactics” and using the “same failed strategy they tried to inflict on the WGA.”

On October 18, after Netflix stated in its Q3 earnings report that talks were “ongoing” and Sarandos said the guild “really broke our momentum” towards a deal, Crabtree-Ireland called BS. “The best way to reach a deal and end this strike is for him and the other CEOs to end their walkout from the bargaining table and resume negotiations,” the SAG-AFTRA national director and chief negotiator told Deadline. “We have been and remain ready to continue talks – every day.”

After an appreciated but DOA bid by George Clooney and other A-listers to intervene in getting talks restarted, it looked like the actors strike would pass the 100-day milestone with no end in sight. Then, on October 21 , after Drescher hit out at the “AMPTPs strategy of non-negotiation” and “a blatant propaganda attempt to discredit union leadership and divide our solidarity,” Bob Iger made a call to Crabtree-Ireland and asked to start a new round of talks.

At 3 p.m. PT on the strike’s 100th day, SAG-AFTRA and the AMPTP put out a joint statement that they were heading back to the bargaining table on October 24 at the guild’s headquarters. That first day of negotiations between the parties was “not great,” according to a well-positioned source. As the studios put forth a new offer they hoped would end the stalemate over “success-based compensation,” the guild proved unmoved, but also open to further discussion.

Although the parties had agreed to meet on October 25, the guild asked that morning to take the day to go over the studios’ proposal of increased bonuses based on the success of streaming shows and movies and a further rise in minimum rates. “It’s a step in the right direction and the negotiating committee is taking the time to do a deep review,” a guild source told Deadline.

The two sides sat down again face-to-face around noon on October 26 with Crabtree-Ireland telling Deadline he was “cautiously optimistic” about deliberations with the studios. The guild slide across the table a self-described “comprehensive counter” that attempted to move the two sides closer together, sources said. As open letters from both supportive and impatient guild members flew around town, the AMPTP and SAG-AFTRA’s negotiating committee were back in active talks on October 27. With both sides taking October 30 to be “working independently,” virtual deliberations bled into the weekend with the parties trying to bridge their differences.

On Halloween and in the early days of November, the parties met again. As the parties got “closer and closer,” as a guild source told Deadline, on issues, Crabtree-Ireland and Lombardini continued conferring directly, with breakout groups of lawyers and other specialists huddled in search of a deal – successfully we now know. Followed by two days of consultation by the guild, the November 3 delivery of the studios’ response to the guild’s latest counter and SAG-AFTRA’s November 6 counter response saw the two sides find an AI compromise and began moving things into what we now know was the final phase.

It took an unexpected strike by actors guild (who many studios execs thought were bluffing despite an overwhelming strike authorization mandate), a lot of moving pieces, guild solidarity, and some hard negotiating sessions to get there.

The actors union joined the WGA on the picket lines when it went on strike July 14, creating Hollywood’s first joint strike in more than 60 years. There were a lot of hot summer days when the labor battle remained at a stalemate.

But things shifted after Labor Day. The WGA reached a deal with the AMPTP on September 24 after five months on the picket lines and a final five intense days of deliberations that included the CEO Gang of Four for most of those last sessions. The WGA leadership approved the tentative agreement and ended the strike at 12:01 a.m. PT on September 27. WGA members ratified the deal by a wide margin October 9.

As exclusively reported by Deadline on September 26, the studios and SAG-AFTRA intended to ride the wave of the WGA deal to set meetings within a week or so on their own talks. However, as the goodwill of the WGA’s successful negotiations faded into bitter public call-outs from leaders on both sides, many feared, even with a new round of talks, the actors strike could last well into the holidays, ruining any chance at a partial broadcast networks season and hobbling the 2024 movie slate.

That catastrophe seems to have been averted now.

[kazeofthemagun]

More on Vodya Houses:

[Massive trigger warnings for racism, slavery, ableism, eugenics, AI, unethical science.]

The concept of Value: idea that every living being has to contribute towards global "value" in some way: either by production of goods, maintaining the ecosystem, research (production of global knowledge) or, failing that, slave labor. Value is often perceived egotistically, with whatever benefits the Vodya House being "valuable" and the rest, not. This leads most Vodya Houses to harbor an innate disdain for other forms of life, especially those that take no part in Vodya's own ecosystem and thus, serve no purpose in its existence. According to the Value Doctrine, the only type of value to be had from such life forms is slave labor.

Beings that are considered unable to provide Value legally lose rights to their own existence. This belief leads to horrific ableism, both mental and physical, among the Vodya, with heavily disabled individuals often being culled. Lesser degrees of "devaluation" predispose the individual to be shifted lower in the work hierarchy, eventually leading to slavery. Most proud members of the Vodya race would much rather die than be reduced to servants, however. This is hypocritical towards their own beliefs, as they openly preach slavery to be the more valuable alternative to death.

The Council of Value: each House possesses their own Council, which usually consists of the Chairs of their respective Cathedrals (with Cathedrals as homes to specific fields of scientific research, such as: Biosynergetics, Technosynergetics, Logistics, Physics, Chemistry, Thaumaturgichemistry, Mathematics, Geosystemics, Medicine, Social Systemics.)

A Chair is most often the lead Mind of their respective field, as in the scientist with the highest overall equivalent to our "impact factor", which is a scoring system used in science.

The Council of Value is the defacto ruling body of the House, the advisors of the Head of the House, who is a political representative and practically always a Chair themself. The Council's job is to decide on the optimal course of action for the House's development, as defined by the maximization of Value. The Council decides whether to approve experiments and pathways of development, evaluating the resource cost vs potential resource production. For this purpose, they often employ the House's Nexus Mind, an advanced risk management AI program.

Notable Vodyanoi:

Pist Shaz XI, Eleventh Head of Shaz. Chair of Technosynergetics, with multiple advanced achievements in related fields. A self-proclaimed Lord of the Seas, he ran House Shaz in an authoritarian manner with several contigents of neural-chipped and bioengineered thralls at his command - couresy of his collabiration with the Shaz Chair of Biosynergetics. He also possessed several squads of specialized Wonderlandian mercenaries as his private army. Ever since he began work on the Ocean Puzzle, he had spent most of his time in a private palace away from the main settlement of House Shaz, both for safety reasons and out of vanity. He was 300+ years old at time of death.

Xel Ort V, Fifth Head of House Ort at tender young age of 37. Heir to the House as per aristocratic nepotism - Ort are more traditional and value genetic lines. Royal children tend to be genetically engineered to inherit most desirable traits, maximizing intellectual ability. She does not yet possess Chairhood in any of the Council's fields, being an undergrad in the Cathedral of Thaumaturgichemistry. Despite this, her achievements are already remarkable and she had set out to further her Mist research in Wonderland, finding work with Anarchy. Still, being saddled with this much responsibility at a young age had left her with major anxiety issues and shaken her personal Value, as well as her political position. Currently on a quest to reaffirm her worth both to herself and to the Ort Council; Struggling with the concept of Value versus morality.

[thetechempire]

YouTube will use AI to generate ideas, titles, and even full videos

🔴 Artificial intelligence is increasingly integrated into Google's product offerings, and YouTube is adopting new AI technologies to assist creators in producing content. During the Made on YouTube event in New York City, the platform announced several AI-related features designed to enhance the video creation process, potentially transforming how creators approach their projects.

🔴 One significant feature is the new Inspiration tab in the YouTube Studio app, which has been tested in a limited capacity. This AI-powered tool provides creators with video concepts, titles, thumbnails, outlines, and even the initial lines of their videos. While framed as a brainstorming aid, these AI-generated suggestions may be particularly effective at optimizing content for the YouTube algorithm.

🔴 Additionally, YouTube is integrating Veo, a powerful DeepMind video model, into YouTube Shorts through the "Dream Screen" feature. This allows creators to utilize AI-generated backgrounds and produce videos with clips up to six seconds long. Veo will be incorporated directly into the Shorts editor, and footage created with it will be watermarked to indicate its AI origin, emphasizing that the creator's vision remains essential in the final product.

🔴 While these advancements offer exciting prospects for creativity, there are concerns that the platform might see an influx of AI-generated content that lacks diversity and originality. YouTube aims to lower the barrier for becoming a creator, particularly with its Shorts feature, as it competes with platforms like TikTok and Instagram. The company is optimistic that AI can streamline various aspects of content creation, encouraging more creators to engage and produce content.

[probablyasocialecologist]

These claims of an extinction-level threat come from the very same groups creating the technology, and their warning cries about future dangers is drowning out stories on the harms already occurring. There is an abundance of research documenting how AI systems are being used to steal art, control workers, expand private surveillance, and seek greater profits by replacing workforces with algorithms and underpaid workers in the Global South.

The sleight-of-hand trick shifting the debate to existential threats is a marketing strategy, as Los Angeles Times technology columnist Brian Merchant has pointed out. This is an attempt to generate interest in certain products, dictate the terms of regulation, and protect incumbents as they develop more products or further integrate AI into existing ones. After all, if AI is really so dangerous, then why did Altman threaten to pull OpenAI out of the European Union if it moved ahead with regulation? And why, in the same breath, did Altman propose a system that just so happens to protect incumbents: Only tech firms with enough resources to invest in AI safety should be allowed to develop AI.

[...]

First, the industry represents the culmination of various lines of thought that are deeply hostile to democracy. Silicon Valley owes its existence to state intervention and subsidy, at different times working to capture various institutions or wither their ability to interfere with private control of computation. Firms like Facebook, for example, have argued that they are not only too large or complex to break up but that their size must actually be protected and integrated into a geopolitical rivalry with China.

Second, that hostility to democracy, more than a singular product like AI, is amplified by profit-seeking behavior that constructs increasingly larger threats to humanity. It’s Silicon Valley and its emulators worldwide, not AI, that create and finance harmful technologies aimed at surveilling, controlling, exploiting, and killing human beings with little to no room for the public to object. The search for profits and excessive returns, with state subsidy and intervention clearing the way of competition, has and will create a litany of immoral business models and empower brutal regimes alongside “existential” threats. At home, this may look like the surveillance firm and government contractor Palantir creating a deportation machine that terrorizes migrants. Abroad, this may look like the Israeli apartheid state exporting spyware and weapons it has tested on Palestinians.

Third, this combination of a deeply antidemocratic ethos and a desire to seek profits while externalizing costs can’t simply be regulated out of Silicon Valley. These are fundamental attributes of the industry that trace back to the beginning of computation. These origins in optimizing plantations and crushing worker uprisings prefigure the obsession with surveillance and social control that shape what we are told technological innovations are for.

Taken altogether, why should we worry about some far-flung threat of a superintelligent AI when its creators—an insular network of libertarians building digital plantations, surveillance platforms, and killing machines—exist here and now? Their Smaugian hoards, their fundamentalist beliefs about markets and states and democracy, and their track record should be impossible to ignore.

[shruti3802]

Exploring Generative AI: Unleashing Creativity through Algorithms

Generative AI, a fascinating branch of artificial intelligence, has been making waves across various fields from art and music to literature and design. At its core, generative AI enables computers to autonomously produce content that mimics human creativity, leveraging complex algorithms and vast datasets.

One of the most compelling applications of generative AI is in the realm of art. Using techniques such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs), AI systems can generate original artworks that blur the line between human and machine creativity. Artists and researchers alike are exploring how these algorithms can inspire new forms of expression or augment traditional creative processes.

In the realm of music, generative AI algorithms can compose melodies, harmonies, and even entire pieces that resonate with listeners. By analyzing existing compositions and patterns, AI can generate music that adapts to different styles or moods, providing musicians with novel ideas and inspirations.

Literature and storytelling have also been transformed by generative AI. Natural Language Processing (NLP) models can generate coherent and engaging narratives, write poetry, or even draft news articles. While these outputs may still lack the depth of human emotional understanding, they showcase AI's potential to assist writers, editors, and journalists in content creation and ideation.

Beyond the arts, generative AI has practical applications in fields like healthcare, where it can simulate biological processes or generate synthetic data for research purposes. In manufacturing and design, AI-driven generative design can optimize product designs based on specified parameters, leading to more efficient and innovative solutions.

However, the rise of generative AI also raises ethical considerations, such as intellectual property rights, bias in generated content, and the societal impact on creative industries. As these technologies continue to evolve, it's crucial to navigate these challenges responsibly and ensure that AI augments human creativity rather than replacing it.

In conclusion, generative AI represents a groundbreaking frontier in technology, unleashing new possibilities across creative disciplines and beyond. As researchers push the boundaries of what AI can achieve, the future promises exciting developments that could redefine how we create, innovate, and interact with technology in the years to come.

If you want to become a Generative AI Expert in India join the Digital Marketing class from Abhay Ranjan

[govindhtech]

Agilex 3 FPGAs: Next-Gen Edge-To-Cloud Technology At Altera

Agilex 3 FPGA

Today, Altera, an Intel company, launched a line of FPGA hardware, software, and development tools to expand the market and use cases for its programmable solutions. Altera unveiled new development kits and software support for its Agilex 5 FPGAs at its annual developer’s conference, along with fresh information on its next-generation, cost-and power-optimized Agilex 3 FPGA.

Altera

Why It Matters

Altera is the sole independent provider of FPGAs, offering complete stack solutions designed for next-generation communications infrastructure, intelligent edge applications, and high-performance accelerated computing systems. Customers can get adaptable hardware from the company that quickly adjusts to shifting market demands brought about by the era of intelligent computing thanks to its extensive FPGA range. With Agilex FPGAs loaded with AI Tensor Blocks and the Altera FPGA AI Suite, which speeds up FPGA development for AI inference using well-liked frameworks like TensorFlow, PyTorch, and OpenVINO toolkit and tested FPGA development flows, Altera is leading the industry in the use of FPGAs in AI inference workload

Intel Agilex 3

What Agilex 3 FPGAs Offer

Designed to satisfy the power, performance, and size needs of embedded and intelligent edge applications, Altera today revealed additional product details for its Agilex 3 FPGA. Agilex 3 FPGAs, with densities ranging from 25K-135K logic elements, offer faster performance, improved security, and higher degrees of integration in a smaller box than its predecessors.

An on-chip twin Cortex A55 ARM hard processor subsystem with a programmable fabric enhanced with artificial intelligence capabilities is a feature of the FPGA family. Real-time computation for time-sensitive applications such as industrial Internet of Things (IoT) and driverless cars is made possible by the FPGA for intelligent edge applications. Agilex 3 FPGAs give sensors, drivers, actuators, and machine learning algorithms a smooth integration for smart factory automation technologies including robotics and machine vision.

Agilex 3 FPGAs provide numerous major security advancements over the previous generation, such as bitstream encryption, authentication, and physical anti-tamper detection, to fulfill the needs of both defense and commercial projects. Critical applications in industrial automation and other fields benefit from these capabilities, which guarantee dependable and secure performance.

Agilex 3 FPGAs offer a 1.9×1 boost in performance over the previous generation by utilizing Altera’s HyperFlex architecture. By extending the HyperFlex design to Agilex 3 FPGAs, high clock frequencies can be achieved in an FPGA that is optimized for both cost and power. Added support for LPDDR4X Memory and integrated high-speed transceivers capable of up to 12.5 Gbps allow for increased system performance.

Agilex 3 FPGA software support is scheduled to begin in Q1 2025, with development kits and production shipments following in the middle of the year.

How FPGA Software Tools Speed Market Entry

Quartus Prime Pro

The Latest Features of Altera’s Quartus Prime Pro software, which gives developers industry-leading compilation times, enhanced designer productivity, and expedited time-to-market, are another way that FPGA software tools accelerate time-to-market. With the impending Quartus Prime Pro 24.3 release, enhanced support for embedded applications and access to additional Agilex devices are made possible.

Agilex 5 FPGA D-series, which targets an even wider range of use cases than Agilex 5 FPGA E-series, which are optimized to enable efficient computing in edge applications, can be designed by customers using this forthcoming release. In order to help lower entry barriers for its mid-range FPGA family, Altera provides software support for its Agilex 5 FPGA E-series through a free license in the Quartus Prime Software.

Support for embedded applications that use Altera’s RISC-V solution, the Nios V soft-core processor that may be instantiated in the FPGA fabric, or an integrated hard-processor subsystem is also included in this software release. Agilex 5 FPGA design examples that highlight Nios V features like lockstep, complete ECC, and branch prediction are now available to customers. The most recent versions of Linux, VxWorks, and Zephyr provide new OS and RTOS support for the Agilex 5 SoC FPGA-based hard processor subsystem.

How to Begin for Developers

In addition to the extensive range of Agilex 5 and Agilex 7 FPGAs-based solutions available to assist developers in getting started, Altera and its ecosystem partners announced the release of 11 additional Agilex 5 FPGA-based development kits and system-on-modules (SoMs).

Developers may quickly transition to full-volume production, gain firsthand knowledge of the features and advantages Agilex FPGAs can offer, and easily and affordably access Altera hardware with FPGA development kits.

Kits are available for a wide range of application cases and all geographical locations. To find out how to buy, go to Altera’s Partner Showcase website.

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