Cognition Emerges From Stealth To Launch AI Software Engineer ‘Devin’

Longtime Slashdot reader ahbond shares a report from VentureBeat: Today, Cognition, a recently formed AI startup backed by Peter Thiel’s Founders Fund and tech industry leaders including former Twitter executive Elad Gil and Doordash co-founder Tony Xu, announced a fully autonomous AI software engineer called “Devin.” While there are multiple coding assistants out there, including the famous Github Copilot, Devin is said to stand out from the crowd with its ability to handle entire development projects end-to-end, right from writing the code and fixing the bugs associated with it to final execution. This is the first offering of this kind and even capable of handling projects on Upwork, the startup has demonstrated. […]

In a blog post today on Cognition’s website, Scott Wu, the founder and CEO of Cognition and an award-winning sports coder, explained Devin can access common developer tools, including its own shell, code editor and browser, within a sandboxed compute environment to plan and execute complex engineering tasks requiring thousands of decisions. The human user simply types a natural language prompt into Devin’s chatbot style interface, and the AI software engineer takes it from there, developing a detailed, step-by-step plan to tackle the problem. It then begins the project using its developer tools, just like how a human would use them, writing its own code, fixing issues, testing and reporting on its progress in real-time, allowing the user to keep an eye on everything as it works. […]

According to demos shared by Wu, Devin is capable of handling a range of tasks in its current form. This includes common engineering projects like deploying and improving apps/websites end-to-end and finding and fixing bugs in codebases to more complex things like setting up fine-tuning for a large language model using the link to a research repository on GitHub or learning how to use unfamiliar technologies. In one case, it learned from a blog post how to run the code to produce images with concealed messages. Meanwhile, in another, it handled an Upwork project to run a computer vision model by writing and debugging the code for it. In the SWE-bench test, which challenges AI assistants with GitHub issues from real-world open-source projects, the AI software engineer was able to correctly resolve 13.86% of the cases end-to-end — without any assistance from humans. In comparison, Claude 2 could resolve just 4.80% while SWE-Llama-13b and GPT-4 could handle 3.97% and 1.74% of the issues, respectively. All these models even required assistance, where they were told which file had to be fixed. Currently, Devin is available only to a select few customers. Bloomberg journalist Ashlee Vance wrote a piece about his experience using it here.

“The Doom of Man is at hand,” captions Slashdot reader ahbond. “It will start with the low-hanging Jira tickets, and in a year or two, able to handle 99% of them. In the short term, software engineers may become like bot farmers, herding 10-1000 bots writing code, etc. Welcome to the future.”

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Qualcomm Launches First True ‘App Store’ For AI With 75 Free Models

Wayne Williams reports via TechRadar: Qualcomm has unveiled its AI Hub, an all-inclusive library of pre-optimized AI models ready for use on devices running on Snapdragon and Qualcomm platforms. These models support a wide range of applications including natural language processing, computer vision, and anomaly detection, and are designed to deliver high performance with minimal power consumption, a critical factor for mobile and edge devices. The AI Hub library currently includes more than 75 popular AI and generative AI models including Whisper, ControlNet, Stable Diffusion, and Baichuan 7B. All models are bundled in various runtimes and are optimized to leverage the Qualcomm AI Engine’s hardware acceleration across all cores (NPU, CPU, and GPU). According to Qualcomm, they’ll deliver four times faster inferencing times.

The AI Hub also handles model translation from the source framework to popular runtimes automatically. It works directly with the Qualcomm AI Engine direct SDK and applies hardware-aware optimizations. Developers can search for models based on their needs, download them, and integrate them into their applications, saving time and resources. The AI Hub also provides tools and resources for developers to customize these models, and they can fine-tune them using the Qualcomm Neural Processing SDK and the AI Model Efficiency Toolkit, both available on the platform.

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The Intercept, Raw Story, and AlterNet Sue OpenAI and Microsoft

The Intercept, Raw Story, and AlterNet have filed separate lawsuits against OpenAI and Microsoft, alleging copyright infringement and the removal of copyright information while training AI models. The Verge reports: The publications said ChatGPT “at least some of the time” reproduces “verbatim or nearly verbatim copyright-protected works of journalism without providing author, title, copyright or terms of use information contained in those works.” According to the plaintiffs, if ChatGPT trained on material that included copyright information, the chatbot “would have learned to communicate that information when providing responses.”

Raw Story and AlterNet’s lawsuit goes further (PDF), saying OpenAI and Microsoft “had reason to know that ChatGPT would be less popular and generate less revenue if users believed that ChatGPT responses violated third-party copyrights.” Both Microsoft and OpenAI offer legal cover to paying customers in case they get sued for violating copyright for using Copilot or ChatGPT Enterprise. The lawsuits say that OpenAI and Microsoft are aware of potential copyright infringement. As evidence, the publications point to how OpenAI offers an opt-out system so website owners can block content from its web crawlers. The New York Times also filed a lawsuit in December against OpenAI, claiming ChatGPT faithfully reproduces journalistic work. OpenAI claims the publication exploited a bug on the chatbot to regurgitate its articles.

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Google Admits Gemini Is ‘Missing the Mark’ With Image Generation of Historical People

Google’s Gemini AI chatbot is under fire for generating historically inaccurate images, particularly when depicting people from different eras and nationalities. Google acknowledges the issue and is actively working to refine Gemini’s accuracy, emphasizing that while diversity in image generation is valued, adjustments are necessary to meet historical accuracy standards. 9to5Google reports: The Twitter/X post in particular that brought this issue to light showed prompts to Gemini asking for the AI to generate images of Australian, American, British, and German women. All four prompts resulted in images of women with darker skin tones, which, as Google’s Jack Krawcyczk pointed out, is not incorrect, but may not be what is expected.

But a bigger issue that was noticed in the wake of that post was that Gemini also struggles to accurately depict human beings in a historical context, with those being depicted often having darker skin tones or being of particular nationalities that are not historically accurate. Google, in a statement posted to Twitter/X, admits that Gemini AI image generation is “missing the mark” on historical depictions and that the company is working to improve it. Google also does say that the diversity represented in images generated by Gemini is “generally a good thing,” but it’s clear some fine-tuning needs to happen. Further reading: Why Google’s new AI Gemini accused of refusing to acknowledge the existence of white people (The Daily Dot)

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Thanks to Machine Learning, Scientist Finally Recover Text From The Charred Scrolls of Vesuvius

The great libraries of the ancient classical world are “legendary… said to have contained stacks of texts,” writes ScienceAlert. But from Rome to Constantinople, Athens to Alexandria, only one collection survived to the present day.

And here in 2024, “we can now start reading its contents.”

A worldwide competition to decipher the charred texts of the Villa of Papyri — an ancient Roman mansion destroyed by the eruption of Mount Vesuvius — has revealed a timeless infatuation with the pleasures of music, the color purple, and, of course, the zingy taste of capers. The so-called Vesuvius challenge was launched a few years ago by computer scientist Brent Seales at the University of Kentucky with support from Silicon Valley investors. The ongoing ‘master plan’ is to build on Seales’ previous work and read all 1,800 or so charred papyri from the ancient Roman library, starting with scrolls labeled 1 to 4.

In 2023, the annual gold prize was awarded to a team of three students, who recovered four passages containing 140 characters — the longest extractions yet. The winners are Youssef Nader, Luke Farritor, and Julian Schilliger. “After 275 years, the ancient puzzle of the Herculaneum Papyri has been solved,” reads the Vesuvius Challenge Scroll Prize website. “But the quest to uncover the secrets of the scrolls is just beginning….” Only now, with the advent of X-ray tomography and machine learning, can their inky words be pulled from the darkness of carbon.
A few months ago students deciphered a single word — “purple,” according to the article. But “That winning code was then made available for all competitors to build upon.”
Within three months, passages in Latin and Greek were blooming from the blackness, almost as if by magic. The team with the most readable submission at the end of 2023 included both previous finders of the word ‘purple’. Their unfurling of scroll 1 is truly impressive and includes more than 11 columns of text. Experts are now rushing to translate what has been found. So far, about 5 percent of the scroll has been unrolled and read to date. It is not a duplicate of past work, scholars of the Vesuvius Challenge say, but a “never-before-seen text from antiquity.”
One line reads: “In the case of food, we do not right away believe things that are scarce to be absolutely more pleasant than those which are abundant.”

Thanks to davidone (Slashdot reader #12,252) for sharing the article.

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Microsoft President: ‘You Can’t Believe Every Video You See or Audio You Hear’

“We’re currently witnessing a rapid expansion in the abuse of these new AI tools by bad actors,” writes Microsoft VP Brad Smith, “including through deepfakes based on AI-generated video, audio, and images.

“This trend poses new threats for elections, financial fraud, harassment through nonconsensual pornography, and the next generation of cyber bullying.” Microsoft found its own tools being used in a recently-publicized episode, and the VP writes that “We need to act with urgency to combat all these problems.”

Microsoft’s blog post says they’re “committed as a company to a robust and comprehensive approach,” citing six different areas of focus:

A strong safety architecture. This includes “ongoing red team analysis, preemptive classifiers, the blocking of abusive prompts, automated testing, and rapid bans of users who abuse the system… based on strong and broad-based data analysis.”
Durable media provenance and watermarking. (“Last year at our Build 2023 conference, we announced media provenance capabilities that use cryptographic methods to mark and sign AI-generated content with metadata about its source and history.”)
Safeguarding our services from abusive content and conduct. (“We are committed to identifying and removing deceptive and abusive content” hosted on services including LinkedIn and Microsoft’s Gaming network.)
Robust collaboration across industry and with governments and civil society. This includes “others in the tech sector” and “proactive efforts” with both civil society groups and “appropriate collaboration with governments.”
Modernized legislation to protect people from the abuse of technology. “We look forward to contributing ideas and supporting new initiatives by governments around the world.”
Public awareness and education. “We need to help people learn how to spot the differences between legitimate and fake content, including with watermarking. This will require new public education tools and programs, including in close collaboration with civil society and leaders across society.”

Thanks to long-time Slashdot reader theodp for sharing the article

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Will ‘Precision Agriculture’ Be Harmful to Farmers?

Modern U.S. farming is being transformed by precision agriculture, writes Paul Roberts, the founder of securepairs.org and Editor in Chief at Security Ledger.

Theres autonomous tractors and “smart spraying” systems that use AI-powered cameras to identify weeds, just for starters. “Among the critical components of precision agriculture: Internet- and GPS connected agricultural equipment, highly accurate remote sensors, ‘big data’ analytics and cloud computing…”

As with any technological revolution, however, there are both “winners” and “losers” in the emerging age of precision agriculture… Precision agriculture, once broadly adopted, promises to further reduce the need for human labor to run farms. (Autonomous equipment means you no longer even need drivers!) However, the risks it poses go well beyond a reduction in the agricultural work force. First, as the USDA notes on its website: the scale and high capital costs of precision agriculture technology tend to favor large, corporate producers over smaller farms. Then there are the systemic risks to U.S. agriculture of an increasingly connected and consolidated agriculture sector, with a few major OEMs having the ability to remotely control and manage vital equipment on millions of U.S. farms… (Listen to my podcast interview with the hacker Sick Codes, who reverse engineered a John Deere display to run the Doom video game for insights into the company’s internal struggles with cybersecurity.)

Finally, there are the reams of valuable and proprietary environmental and operational data that farmers collect, store and leverage to squeeze the maximum productivity out of their land. For centuries, such information resided in farmers’ heads, or on written or (more recently) digital records that they owned and controlled exclusively, typically passing that knowledge and data down to succeeding generation of farm owners. Precision agriculture technology greatly expands the scope, and granularity, of that data. But in doing so, it also wrests it from the farmer’s control and shares it with equipment manufacturers and service providers — often without the explicit understanding of the farmers themselves, and almost always without monetary compensation to the farmer for the data itself. In fact, the Federal Government is so concerned about farm data they included a section (1619) on “information gathering” into the latest farm bill.
Over time, this massive transfer of knowledge from individual farmers or collectives to multinational corporations risks beggaring farmers by robbing them of one of their most vital assets: data, and turning them into little more than passive caretakers of automated equipment managed, controlled and accountable to distant corporate masters.

Weighing in is Kevin Kenney, a vocal advocate for the “right to repair” agricultural equipment (and also an alternative fuel systems engineer at Grassroots Energy LLC). In the interview, he warns about the dangers of tying repairs to factory-installed firmware, and argues that its the long-time farmer’s “trade secrets” that are really being harvested today. The ultimate beneficiary could end up being the current “cabal” of tractor manufacturers.

“While we can all agree that it’s coming…the question is who will own these robots?”

First, we need to acknowledge that there are existing laws on the books which for whatever reason, are not being enforced. The FTC should immediately start an investigation into John Deere and the rest of the ‘Tractor Cabal’ to see to what extent farmers’ farm data security and privacy are being compromised. This directly affects national food security because if thousands- or tens of thousands of tractors’ are hacked and disabled or their data is lost, crops left to rot in the fields would lead to bare shelves at the grocery store… I think our universities have also been delinquent in grasping and warning farmers about the data-theft being perpetrated on farmers’ operations throughout the United States and other countries by makers of precision agricultural equipment.

Thanks to long-time Slashdot reader chicksdaddy for sharing the article.

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