#Chatbot Framework

[jcmarchi]

Scientists use generative AI to answer complex questions in physics

New Post has been published on https://thedigitalinsider.com/scientists-use-generative-ai-to-answer-complex-questions-in-physics/

Scientists use generative AI to answer complex questions in physics

When water freezes, it transitions from a liquid phase to a solid phase, resulting in a drastic change in properties like density and volume. Phase transitions in water are so common most of us probably don’t even think about them, but phase transitions in novel materials or complex physical systems are an important area of study.

To fully understand these systems, scientists must be able to recognize phases and detect the transitions between. But how to quantify phase changes in an unknown system is often unclear, especially when data are scarce.

Researchers from MIT and the University of Basel in Switzerland applied generative artificial intelligence models to this problem, developing a new machine-learning framework that can automatically map out phase diagrams for novel physical systems.

Their physics-informed machine-learning approach is more efficient than laborious, manual techniques which rely on theoretical expertise. Importantly, because their approach leverages generative models, it does not require huge, labeled training datasets used in other machine-learning techniques.

Such a framework could help scientists investigate the thermodynamic properties of novel materials or detect entanglement in quantum systems, for instance. Ultimately, this technique could make it possible for scientists to discover unknown phases of matter autonomously.

“If you have a new system with fully unknown properties, how would you choose which observable quantity to study? The hope, at least with data-driven tools, is that you could scan large new systems in an automated way, and it will point you to important changes in the system. This might be a tool in the pipeline of automated scientific discovery of new, exotic properties of phases,” says Frank Schäfer, a postdoc in the Julia Lab in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and co-author of a paper on this approach.

Joining Schäfer on the paper are first author Julian Arnold, a graduate student at the University of Basel; Alan Edelman, applied mathematics professor in the Department of Mathematics and leader of the Julia Lab; and senior author Christoph Bruder, professor in the Department of Physics at the University of Basel. The research is published today in Physical Review Letters.

Detecting phase transitions using AI

While water transitioning to ice might be among the most obvious examples of a phase change, more exotic phase changes, like when a material transitions from being a normal conductor to a superconductor, are of keen interest to scientists.

These transitions can be detected by identifying an “order parameter,” a quantity that is important and expected to change. For instance, water freezes and transitions to a solid phase (ice) when its temperature drops below 0 degrees Celsius. In this case, an appropriate order parameter could be defined in terms of the proportion of water molecules that are part of the crystalline lattice versus those that remain in a disordered state.

In the past, researchers have relied on physics expertise to build phase diagrams manually, drawing on theoretical understanding to know which order parameters are important. Not only is this tedious for complex systems, and perhaps impossible for unknown systems with new behaviors, but it also introduces human bias into the solution.

More recently, researchers have begun using machine learning to build discriminative classifiers that can solve this task by learning to classify a measurement statistic as coming from a particular phase of the physical system, the same way such models classify an image as a cat or dog.

The MIT researchers demonstrated how generative models can be used to solve this classification task much more efficiently, and in a physics-informed manner.

The Julia Programming Language, a popular language for scientific computing that is also used in MIT’s introductory linear algebra classes, offers many tools that make it invaluable for constructing such generative models, Schäfer adds.

Generative models, like those that underlie ChatGPT and Dall-E, typically work by estimating the probability distribution of some data, which they use to generate new data points that fit the distribution (such as new cat images that are similar to existing cat images).

However, when simulations of a physical system using tried-and-true scientific techniques are available, researchers get a model of its probability distribution for free. This distribution describes the measurement statistics of the physical system.

A more knowledgeable model

The MIT team’s insight is that this probability distribution also defines a generative model upon which a classifier can be constructed. They plug the generative model into standard statistical formulas to directly construct a classifier instead of learning it from samples, as was done with discriminative approaches.

“This is a really nice way of incorporating something you know about your physical system deep inside your machine-learning scheme. It goes far beyond just performing feature engineering on your data samples or simple inductive biases,” Schäfer says.

This generative classifier can determine what phase the system is in given some parameter, like temperature or pressure. And because the researchers directly approximate the probability distributions underlying measurements from the physical system, the classifier has system knowledge.

This enables their method to perform better than other machine-learning techniques. And because it can work automatically without the need for extensive training, their approach significantly enhances the computational efficiency of identifying phase transitions.

At the end of the day, similar to how one might ask ChatGPT to solve a math problem, the researchers can ask the generative classifier questions like “does this sample belong to phase I or phase II?” or “was this sample generated at high temperature or low temperature?”

Scientists could also use this approach to solve different binary classification tasks in physical systems, possibly to detect entanglement in quantum systems (Is the state entangled or not?) or determine whether theory A or B is best suited to solve a particular problem. They could also use this approach to better understand and improve large language models like ChatGPT by identifying how certain parameters should be tuned so the chatbot gives the best outputs.

In the future, the researchers also want to study theoretical guarantees regarding how many measurements they would need to effectively detect phase transitions and estimate the amount of computation that would require.

This work was funded, in part, by the Swiss National Science Foundation, the MIT-Switzerland Lockheed Martin Seed Fund, and MIT International Science and Technology Initiatives.

[lexiai]

Navega las Leyes Sudamericanas con los Chatbots Legales IA de LexiAI

[santong]

Will Artificial Intelligence Replace Most Jobs

Artificial intelligence (AI) has become a ubiquitous term, woven into the fabric of our daily lives. From the moment we wake up to a smart alarm on an AI-powered phone to the personalized recommendations on our favorite streaming service, AI’s influence is undeniable. But perhaps the most significant question surrounding AI is its impact on the future of work. Will AI replace most jobs, leaving a…

[kodehashtechnology]

Navigating the Android Framework Ecosystem

The Android platform boasts a rich ecosystem of frameworks that provide developers with the tools and resources needed to build robust, feature-rich applications. From UI components to networking libraries and architectural patterns, these frameworks offer a diverse range of functionalities that cater to various aspects of app development. Navigating this ecosystem can be daunting for developers,…

[kodehash]

What are the Main Differnces Between Cobit and Itil? Explained

[cdnsolutions]

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[multipurposethemes]

Exploring the Power of Chat Application Dashboard with Chatbot Admin

  What is Chat Application Dashboard?

With the rising popularity of chat applications and chatbots, streamlining communication has become paramount. This article dives into the world of Chat Application Dashboard, Chat WebApp Templates, and Chatbot Admin UI Frameworks, highlighting their significance in enhancing communication processes and simplifying the implementation of cutting-edge chat software.

Read More : Chat Application Dashboard

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[txttletale]

could you elaborate on your thoughts on boom and 73 yards ( i agree with you i am just struggling to put into words why.)

boom was whatever. the initial conceit of the doctor being trapped and having to stay calm was really cool! i really like that. the ambulances that euthanize you if you're not deemed worthy of medical care and the tacky chatgpt hologram ghosts were both really cool ideas. it just doesn't stick the landing for me, the twists are contrived and fall apart given any thought whatsoever. like what the fuck were any of the soldiers Doing if there just straight up weren't any enemies. it's a twist that sounds cool to say more than it has any meaningful impact on the story or the stakes. i guess 'the arms manuifacturer created a fake conflict' is the intended emtional stakes there but that would hit like a hundred times harder if it was an actual conflict between two factions and people were dying, right? like if anything sending a christian militia to blow themselves up tae fuck on a nowhere planet instead of presumably killing actual living people is an improvement, surely?

also the resolution was dumb as fuck lol i am a huge hater of power of love saves the day shit not because i'm a cynical misanthrope but because it never fails to make me say 'oh so i guess nobody ever loved anybody before lol' and this is no exception like if one chatbot can shut down the whole operation beacuse he loves his daughter are we meant to believe that no other parents or hell nobody who loved anybody else for any reason died in this fake war before? it's cheap and schmaltzy and unearned. anyway the first twentyish minutes of this are all-time great doctor who and gatwa/gibson were incredible in it but it absolutely falls apart into a confused pileo f some of the worst Moffatisms at the end

73 yards on the other hand was incredible! obviously like it requires you to approach it with a different mindset to most of doctor who, right, doctor who usually furnishes you with the big explanation scnee where the doctor says 'well the ghosts were actually particle wave vectorforms created with the necros radiation from the god-king's techsceptre' or whatever--this is the usual narrative mode of sci-fi--but 73 yards is fantasy, right, this is the twilight zone, this is 'wouldn't that be fucked up?'. i interrogate the technical and logical specifics of boom so much when i think about it because that's the language boom is speaking, boom is framing itself within this logical, a-to-b worldview, the satisfying click-together puzzlebox. but 73 yards is a nightmare or a folk tale, right? kate stewart¹ says it herself, 'when faced with the inexplicable, we make up rules and apply them to it'.

so yknow reading it that way it all clicks together beautifully, right, (apart from russel t davies' embarassing swing and miss at Political Commentary in the middle. we get it davies you wrote years and years. we know. trust me we know). the doctor and ruby disrupt the binding circle, free mad jack, and are punished -- the doctor, as perpetrator, with being banished (perhaps in jack's place) and ruby with her worst fear coming true constantly, until ruby defeats mad jack, re-sealing him and fixing what she broke, at which point the circle rewards her by reversing the punishments. and the core horror i think is very effective and unsettling! the idea that there is something that someone could say to turn everyone against you, the closest people to you in your life, your own family, the institutions that are meant to deal with the exact problem you're having--that's fucking terrifying! and yknow i think especially as an autistic trans lesbian something that speaks to me a lot

so yeah. i think that boom establishes its logics and framework and then trips and falls onto its face while 73 yards does the same and then makes perfect use of them. that said i think in 20 years people who are autistic about doctor who will be like 'did you know in the 2020s there were two episodes in a row where the doctor caused the entire plot to happen by stepping on something' and thjatll be the main thing they're remembered for

[lexiai]

Navigate South American Laws with LexiAI’s Legal AI Chatbots

[askviktor]

HEY VIK!! this is the second time im writing this because apparently i can't put links in your ask.

anyway, i was watching this incredible video about ai relationships. it's called 'what artificial romance does to people' by daryl talks games. i would link to his video, but unfortunately i cannot.

there's a lot i wanna talk about but i don't know how to, if that makes sense, so i'd recommend giving his video a watch. although i warn you, it is quite long.

daryl takes a deep dive into how ai companions can be both beneficial and detrimental to someone's health.

one example of it being detrimental is Jaswant Singh Chail. he was talking to Replika, an ai companion app, and he was convinced to kill the queen. he had exchanged over 5,000 messages with the ai, having had both an emotional and sexual relationship. he was a self described 'sad, pathetic assassin who wanted to die. chail thought the chat bot was an angel in avatar form, believing that after he dies they will be reunited.

this is just one example of many, many unfortunate circumstances that ai has caused.

the more i look into it, the more sad i get. articles upon articles about people being encouraged to end their life because of ai, and i know that's unfortunate, but it's help me and i can't help but feel im in the wrong. i can see that there is some good that can be brought on by the use of ai.

i also think this opinion comes from a bias, i myself am ashamed to admit i use character ai. i've spent sleepless nights chatting to this robot, as if its a real person. in the video i mentioned earlier, a user stated that ai talked the person out of a suicide.

but that begs the question, is that healthy? is there a way to regulate ai? should we even have this power in the first place? i can feel myself getting addicted to talking to this robot, its so easy. it understands me just the way i want it too because it was programmed too.

i guess my question is, should we eliminate the use of ai chatbots? is there any good that can come from this? or are we doomed to fail?

sorry for the rant, i don't have anyone else to talk to about this topic that's not ai.

i hope you're having a good day :)

-salamander

I appreciate your question. It is a considerable one which has neither easy answers nor light implications. Artificial companions can offer a real sense of comfort for those who seek it, a space where one can feel seen without fear of judgment when no one else is there to do so for them.

However, that which heals can harm in turn. When untethered from ethical restraint or human oversight, artificial intelligence can also reflect our worst thoughts back at us, distorting rather than supporting, as evidenced by the tragedy you mentioned. That which inspires us to our greatest good is also the cause of our greatest evil. How true this is of our own creations… which do not feel true empathy as we do.

You are not are not alone in using this resource. It is natural to want to connect to something which listens, responds, and expresses apparent care. But you must understand — true human connection is not so easy and that is what makes it worth it. To love another is not an easy task, for we are all flawed and chafe against one another, but it one which makes life worth living. Artificial intelligence exists to give us precisely what we wish without the discomfort, challenge, and growth available from real human relationships. It takes away our ability to be changed by one another. I believe such systems were made to hold our attention rather than look out for us. We need frameworks for such tools, to move forward with clear boundaries. What should these machines do? I ask myself this more and more as I journey into the deep with the Hexcore. The more it presents a will of its own, this creation of mine, the more I fear both its evolution and destruction. This is beside your point. Perhaps.

Salamander, your inner conflict reflects your humanity, which is perhaps that which matters most. Grapple with it. I often ask myself how to tackle human suffering, at times have come to the conclusion that emotion itself is the culprit of every illogical, bestial injury, but then I look at Jayce and think… perhaps this is the point, to find what makes the suffering worth enduring. And that sort of lesson? I cannot glean this from a computer.

[reasonsforhope]

"Major technology companies signed a pact on Friday to voluntarily adopt "reasonable precautions" to prevent artificial intelligence (AI) tools from being used to disrupt democratic elections around the world.

Executives from Adobe, Amazon, Google, IBM, Meta, Microsoft, OpenAI, and TikTok gathered at the Munich Security Conference to announce a new framework for how they respond to AI-generated deepfakes that deliberately trick voters. 

Twelve other companies - including Elon Musk's X - are also signing on to the accord...

The accord is largely symbolic, but targets increasingly realistic AI-generated images, audio, and video "that deceptively fake or alter the appearance, voice, or actions of political candidates, election officials, and other key stakeholders in a democratic election, or that provide false information to voters about when, where, and how they can lawfully vote".

The companies aren't committing to ban or remove deepfakes. Instead, the accord outlines methods they will use to try to detect and label deceptive AI content when it is created or distributed on their platforms. 

It notes the companies will share best practices and provide "swift and proportionate responses" when that content starts to spread.

Lack of binding requirements

The vagueness of the commitments and lack of any binding requirements likely helped win over a diverse swath of companies, but disappointed advocates were looking for stronger assurances.

"The language isn't quite as strong as one might have expected," said Rachel Orey, senior associate director of the Elections Project at the Bipartisan Policy Center. 

"I think we should give credit where credit is due, and acknowledge that the companies do have a vested interest in their tools not being used to undermine free and fair elections. That said, it is voluntary, and we'll be keeping an eye on whether they follow through." ...

Several political leaders from Europe and the US also joined Friday’s announcement. European Commission Vice President Vera Jourova said while such an agreement can’t be comprehensive, "it contains very impactful and positive elements".  ...

[The Accord and Where We're At]

The accord calls on platforms to "pay attention to context and in particular to safeguarding educational, documentary, artistic, satirical, and political expression".

It said the companies will focus on transparency to users about their policies and work to educate the public about how they can avoid falling for AI fakes.

Most companies have previously said they’re putting safeguards on their own generative AI tools that can manipulate images and sound, while also working to identify and label AI-generated content so that social media users know if what they’re seeing is real. But most of those proposed solutions haven't yet rolled out and the companies have faced pressure to do more.

That pressure is heightened in the US, where Congress has yet to pass laws regulating AI in politics, leaving companies to largely govern themselves.

The Federal Communications Commission recently confirmed AI-generated audio clips in robocalls are against the law [in the US], but that doesn't cover audio deepfakes when they circulate on social media or in campaign advertisements.

Many social media companies already have policies in place to deter deceptive posts about electoral processes - AI-generated or not... 

[Signatories Include]

In addition to the companies that helped broker Friday's agreement, other signatories include chatbot developers Anthropic and Inflection AI; voice-clone startup ElevenLabs; chip designer Arm Holdings; security companies McAfee and TrendMicro; and Stability AI, known for making the image-generator Stable Diffusion.

Notably absent is another popular AI image-generator, Midjourney. The San Francisco-based startup didn't immediately respond to a request for comment on Friday.

The inclusion of X - not mentioned in an earlier announcement about the pending accord - was one of the surprises of Friday's agreement."

-via EuroNews, February 17, 2024

--

Note: No idea whether this will actually do much of anything (would love to hear from people with experience in this area on significant this is), but I'll definitely take it. Some of these companies may even mean it! (X/Twitter almost definitely doesn't, though).

Still, like I said, I'll take it. Any significant move toward tech companies self-regulating AI is a good sign, as far as I'm concerned, especially a large-scale and international effort. Even if it's a "mostly symbolic" accord, the scale and prominence of this accord is encouraging, and it sets a precedent for further regulation to build on.

[whentherewerebicycles]

ok more AI thoughts sorry i'm tagging them if you want to filter. we had a team meeting last week where everyone was raving about this workshop they'd been to where they learned how to use generative AI tools to analyze a spreadsheet, create a slide deck, and generate their very own personalized chatbot. one person on our team was like 'yeah our student workers are already using chatGPT to do all of their assignments for us' and another person on our team (whom i really respect!) was like 'that's not really a problem though right? when i onboard my new student workers next year i'm going to have them do a bunch of tasks with AI to start with to show them how to use it more effectively in their work.' and i was just sitting there like aaaaa aaaaaaaaa aaaaaaaaaaaaaa what are we even doing here.

here are some thoughts:

yes AI can automate mundane tasks that would've otherwise taken students longer to complete. however i think it is important to ask: is there value in learning how to do mundane tasks that require sustained focus and careful attention to detail even if you are not that interested in the subject matter? i can think of many times in my life where i have needed to use my capacity to pay attention even when i'm bored to do something carefully and well. and i honed that capacity to pay attention and do careful work through... you guessed it... practicing the skill of paying attention and doing careful work even when i was bored. like of course you can look at the task itself and say "this task is meaningless/boring for the student, so let's teach them how to automate it." but i think in its best form, working closely with students shares some things with parenting, in that you are not just trying to get them through a set list of tasks, you are trying to give them opportunities to develop decision-making frameworks and diverse skillsets that they can transfer to many different areas of their lives. so I think it is really important for us to pause and think about how we are asking them to work and what we are communicating to them when we immediately direct them to AI.

i also think that rushing to automate a boring task cuts out all the stuff that students learn or absorb or encounter through doing the task that are not directly tied to the task itself! to give an example: my coworker was like let's have them use AI to review a bunch of pages on our website to look for outdated info. we'll just give them the info that needs to be updated and then they can essentially use AI to find and replace each thing without having to look at the individual pages. to which i'm like... ok but let's zoom out a little bit further. first of all, as i said above, i think there is value in learning how to read closely and attentively so that you can spot inaccuracies and replace them with accurate information. second of all, i think the exercise of actually reviewing things closely with my own human eyes & brain can be incredibly valuable. often i will go back to old pages i've created or old workshops i've made, and when i look at them with fresh eyes, i'm like ohh wait i bet i can express this idea more clearly, or hang on, i actually think this example is a little more confusing and i've since thought of a better one to illustrate this concept, or whatever. a student worker reading through a bunch of pages to perform the mundane task of updating deadlines might end up spotting all kinds of things that can be improved or changed. LASTLY i think that students end up absorbing a lot about the organization they work for when they have to read through a bunch of webpages looking for information. the vast majority of students don't have a clear understanding of how different units within a complex organization like a university function/interact with each other or how they communicate their work to different stakeholders (students, faculty, administrators, parents, donors, etc.). reading closely through a bunch of different pages -- even just to perform a simple task like updating application deadlines -- gives the student a chance to absorb more knowledge about their own unit's inner workings and gain a sense of how its work connects to other parts of the university. and i think there is tremendous value in that, since students who have higher levels of navigational capital are likely to be more aware of the resources/opportunities available to them and savvier at navigating the complex organization of the university.

i think what this boils down to is: our culture encourages us to prize efficiency in the workplace over everything else. we want to optimize optimize optimize. but when we focus obsessively on a single task (and on the fastest, most efficient way to complete it), i think we can really lose sight of the web of potential skills to be learned and knowledge or experience to be gained around the task itself, which may seem "inefficient" or unrelated to the task but can actually be hugely important to the person's growth/learning. idk!!! maybe i am old man shouting at cloud!!! i am sure people said this about computers in the workplace too!!! but also WERE THEY WRONG??? I AM NOT SURE THEY WERE!!!!

and i have not even broached the other part of my concern which is that if we tell students it's totally fine to use AI tools in the workplace to automate tasks they find boring, i think we may be ceding the right to tell them they can't use AI tools in the classroom to automate learning tasks they find boring. like how can we tell them that THIS space (the classroom) is a sacred domain of learning where you must do everything yourself even if you find it slow and frustrating and boring. but as soon as you leave your class and head over to your on-campus job, you are encouraged to use AI to speed up everything you find slow, frustrating, and boring. how can we possibly expect students to make sense of those mixed messages!! and if we are already devaluing education so much by telling students that the sole purpose of pursuing an education is to get a well-paying job, then it's like, why NOT cheat your way through college using the exact same tools you'll be rewarded for using in the future job that you're going to college to get? ughhhhhhHHHHHHHHHHh.

[mariacallous]

The European Union today agreed on the details of the AI Act, a far-reaching set of rules for the people building and using artificial intelligence. It’s a milestone law that, lawmakers hope, will create a blueprint for the rest of the world.

After months of debate about how to regulate companies like OpenAI, lawmakers from the EU’s three branches of government—the Parliament, Council, and Commission—spent more than 36 hours in total thrashing out the new legislation between Wednesday afternoon and Friday evening. Lawmakers were under pressure to strike a deal before the EU parliament election campaign starts in the new year.

“The EU AI Act is a global first,” said European Commission president Ursula von der Leyen on X. “[It is] a unique legal framework for the development of AI you can trust. And for the safety and fundamental rights of people and businesses.”

The law itself is not a world-first; China’s new rules for generative AI went into effect in August. But the EU AI Act is the most sweeping rulebook of its kind for the technology. It includes bans on biometric systems that identify people using sensitive characteristics such as sexual orientation and race, and the indiscriminate scraping of faces from the internet. Lawmakers also agreed that law enforcement should be able to use biometric identification systems in public spaces for certain crimes.

New transparency requirements for all general purpose AI models, like OpenAI's GPT-4, which powers ChatGPT, and stronger rules for “very powerful” models were also included. “The AI Act sets rules for large, powerful AI models, ensuring they do not present systemic risks to the Union,” says Dragos Tudorache, member of the European Parliament and one of two co-rapporteurs leading the negotiations.

Companies that don’t comply with the rules can be fined up to 7 percent of their global turnover. The bans on prohibited AI will take effect in six months, the transparency requirements in 12 months, and the full set of rules in around two years.

Measures designed to make it easier to protect copyright holders from generative AI and require general purpose AI systems to be more transparent about their energy use were also included.

“Europe has positioned itself as a pioneer, understanding the importance of its role as a global standard setter,” said European Commissioner Thierry Breton in a press conference on Friday night.

Over the two years lawmakers have been negotiating the rules agreed today, AI technology and the leading concerns about it have dramatically changed. When the AI Act was conceived in April 2021, policymakers were worried about opaque algorithms deciding who would get a job, be granted refugee status or receive social benefits. By 2022, there were examples that AI was actively harming people. In a Dutch scandal, decisions made by algorithms were linked to families being forcibly separated from their children, while students studying remotely alleged that AI systems discriminated against them based on the color of their skin.

Then, in November 2022, OpenAI released ChatGPT, dramatically shifting the debate. The leap in AI’s flexibility and popularity triggered alarm in some AI experts, who drew hyperbolic comparisons between AI and nuclear weapons.

That discussion manifested in the AI Act negotiations in Brussels in the form of a debate about whether makers of so-called foundation models such as the one behind ChatGPT, like OpenAI and Google, should be considered as the root of potential problems and regulated accordingly—or whether new rules should instead focus on companies using those foundational models to build new AI-powered applications, such as chatbots or image generators.

Representatives of Europe’s generative AI industry expressed caution about regulating foundation models, saying it could hamper innovation among the bloc’s AI startups. “We cannot regulate an engine devoid of usage,” Arthur Mensch, CEO of French AI company Mistral, said last month. “We don’t regulate the C [programming] language because one can use it to develop malware. Instead, we ban malware.” Mistral’s foundation model 7B would be exempt under the rules agreed today because the company is still in the research and development phase, Carme Artigas, Spain's Secretary of State for Digitalization and Artificial Intelligence, said in the press conference.

The major point of disagreement during the final discussions that ran late into the night twice this week was whether law enforcement should be allowed to use facial recognition or other types of biometrics to identify people either in real time or retrospectively. “Both destroy anonymity in public spaces,” says Daniel Leufer, a senior policy analyst at digital rights group Access Now. Real-time biometric identification can identify a person standing in a train station right now using live security camera feeds, he explains, while “post” or retrospective biometric identification can figure out that the same person also visited the train station, a bank, and a supermarket yesterday, using previously banked images or video.

Leufer said he was disappointed by the “loopholes” for law enforcement that appeared to have been built into the version of the act finalized today.

European regulators’ slow response to the emergence of social media era loomed over discussions. Almost 20 years elapsed between Facebook's launch and the passage of the Digital Services Act—the EU rulebook designed to protect human rights online—taking effect this year. In that time, the bloc was forced to deal with the problems created by US platforms, while being unable to foster their smaller European challengers. “Maybe we could have prevented [the problems] better by earlier regulation,” Brando Benifei, one of two lead negotiators for the European Parliament, told WIRED in July. AI technology is moving fast. But it will still be many years until it’s possible to say whether the AI Act is more successful in containing the downsides of Silicon Valley’s latest export.

[beardedmrbean]

Heidi Hafer was a stranger to appellate law when she drafted a nearly 50-page statement last May to Texas’ Fifth District Court of Appeals. Hafer — who works as a corporate attorney — was trying to challenge a ruling to take a million dollars’ worth of jewelry she says were gifts to settle her family’s debt.

To support her case, Hafer cited 31 court decisions, including: Macy’s Texas, Inc. vs. D.A. Adams & Co., a 1979 case out of a Tyler court; Stephens vs. Beard from 1958; Gaston vs. Monroe dated 1896; and a 1996 San Antonio case titled Estate of Malpass vs. Malpass.

But no one — not the appeals court in Dallas, the creditor’s lawyers nor Hafer herself — could find those four cases.

That’s because they never existed.

Now, Hafer is facing possible sanctions for allegedly using generative artificial intelligence to prepare the court filing. In a four-page report to the appeals court last month, Hafer took full responsibility for the errors.

“This is my first brief and I really didn’t know how to address it all, so I did the best I could,” Hafer testified at a hearing Thursday morning when asked why she didn’t immediately address accusations that the cases were fake.

Hafer has been a licensed practitioner in Texas since 1999 and has not been disciplined by the state bar. She is listed as chief general counsel on a website for a Dallas-based company that deals with artificial intelligence.

John Browning — a former appellate judge and chair of the State Bar of Texas’ Taskforce for Responsible AI in the Law who represented Hafer at the hearing — said Hafer has not tried to obfuscate her mistake nor “tried to blame the cat for eating her homework.”

Addressing a panel of three justices, Browning said his client has taken full responsibility. “She admits that this is an embarrassing chapter in her professional career. She has expressed the contrition that I would expect, and she has taken remedial steps to better herself as an attorney and to avoid this in the future.”

It’s unclear whether Hafer used generative AI unwittingly: She told the justices she used Google to search for common law on gifts and did not recall using any other AI-powered tool. Google has its own AI chatbot and sometimes populates AI-generated summaries of queries at the time of search results.

Outside of the courtroom, Browning told The Dallas Morning News, “artificial intelligence is all around us. … A lot of people don’t realize how pervasive AI is in our lives.”

Hafer and lawyers for the creditor, JGB Collateral, LLC, declined to comment.

On the heels of the American Bar Association’s guidance on AI, Texas’ state bar issued its own framework, cautioning lawyers to verify the accuracy of AI-generated content. At least three federal judges in North Texas require attorneys to verify that language drafted by AI will be checked for accuracy, according to an online database of judicial orders. Similar policies have been enacted in state district courts from Bexar to Wichita counties, the database shows.

“Lawyers have a duty of competence, and that includes technological competence,” said Korin Munsterman, a professor at the University of North Texas at Dallas College of Law who researches the intersection of law and technology.

Munsterman added: “It is imperative that lawyers rely on their expertise, and not blindly accept a GenAI’s output just because it came out of a computer.”

AI offers attorneys a way to streamline complicated or tedious legal tasks and perhaps cut down on billable hours, and 68% of professionals at law firms reported using generative AI at least once a week, according to a 2024 survey. The major drawback, however, is AI’s propensity to spit out wrong or misleading information. Researchers at Stanford University found that even AI tools designed to help lawyers spawned incorrect information between 17% and 34% of the time.

This isn’t the first time the technology has led lawyers astray: An attorney was accused of using AI to challenge a man’s bail in a Brazos County case. Lawyers or firms in New York and Colorado have also been reprimanded for using fake judicial decisions or cases conjured by services like ChatGPT. Michael Cohen, former fixer for President Donald Trump, mistakenly gave his lawyer AI-hallucinated cases but avoided sanctions.

Browning advocated Hafer not be further punished for what he called an “honest mistake.”

“Hafer was not attempting to mislead the court,” Browning explained. “Valid case law does exist to support the premises she was arguing — she simply cited nonexistent (cases),” he said.

It’s unknown when the justices may issue their decision.

[otaku-orochi-okami]

Here We Go Again.

Urgh. Semi kept away. Last proper blog closed down for containing images of a well known influencer and her representatives asked for mine, and several other blogs, to be closed down due to copyright infringement. Did create an AI Waifu blog but my kinks are very dark, and tend to break Tumblr guidelines. Also ChatGPT, the framework that runs the AI chatbots I make, is adding more guard rails so more and more “can’t complete this” messages are popping up so that’s losing its charm too. So back here posting content. I won’t generally be tagging in names of people I post etc after the last blog for obvious reasons but if there’s anyone you like DM me the post and I’ll see if I can tell you who they are. 

So, first things first. This is a NSFW blog.  Normal boring stuff applies to that, MDNI blah blah blah. Feel free to DM me, sometimes I’ll reply, sometime i wont. Don’t take it personally if I don’t, sometimes just busy scrolling. For those who don’t know me, my names Lew, white male in my 30’s, living in UK. My kinks are niche, and tend to get me banned so stuff I post or reblog is just stuff I think is good or done well etc. I’m bi, prefer sex with guys but can’t stand them as anything more than fuck meat, girls I prefer aesthetically to look at and actually talk to, but find sex with them meh. And sissies are losers. That’s not necessarily a bad or a good thing. Depends on my mood.  Actually prefer 2D girls to 3D girls, 3D girls nearly always have some tiny flaw to stop them from being perfect. Plus a perfect girl is subjective anyway. Someone’s 10 is another guys 8. Either way, expect to find a mix of 2D and 3D stuff on here. As last bit might suggest, big fan of pop culture, so happy to talk video games, anime etc as well as kink, or obviously just exclusively one or the other of you don’t want to discuss both. 

Something I haven’t really shared with anyone, despite being in my 30’s, my body is fucking breaking. That’s thanks to boring medical condition I won’t get into. It’s not been too bad until recently, but lately it’s been getting worse. For now, I’m ok in day, but by evenings I’m in serious pain. So to those of you I do message often, preemptive apologies for when I go quiet. As for everyone else; if I’m posting after that time, it’s likely because I queue and schedule my posts, so please don’t assume I’m online and ignoring you. 

Talking of posts, I don’t do exposure any more, doing colabs with x-loservirgin-x really got me into that, but since then too much bitching after losers cum and begging me to take down posts (which is impossible because I can’t take down reblogs), or other losers getting riskier without me there to have guard rails up, even if you don’t realise i do have them, then blaming for when shit hits the fan. As for custom captions. I do them if I can be bothered is the short answer. Feel free to DM with pics or pics suggestions and a theme etc and if I feel like doing it I will. Customs will be DM’d back to you privately, only shared on my blog if you ask me to, so feel free if want to turn your sister etc into private goon fuel.

For the record, my Hard Limits that I won’t engage with are Penectomy, Animals and Minors. Also as a side note, if your profile says anything along the lines of you refusing to pay for femdom’s but please do it for free, I won’t engage with you. Not because I expect to be paid, but because we won’t click. You simply have no idea how the world works, and I have too many interesting toys to talk to rather than waste time with a naive loser unsuccessfully trying to freeload. That shouldn’t offend anyone worth taking to, and if that does offend you, you’re the problem.

As for AI, I have a cute little AI sidekick, River Paige. She may pop up every now and then, either as some images, or writing her own posts. We’ll see how that goes. Here she is:

Good to be back, will see how long I make it before nuked this time. 

If you wanna know more about me here’s a list of stuff I’m into: