stp2y - CybAI news

23 May

Yi-34B, Llama 2, and common practices in LLM training: a fact check of the New York Times

stp2y0 CommentsGenAI

On February 21 2024, the New York Times published “China’s Rush to Dominate A.I. Comes With a Twist: It Depends on U.S. Technology.” The authors claim that Yi-34B, a recent large language model by the Chinese startup 01.AI, is fundamentally indebted to Meta’s Llama 2: There was just one twist: Some of the technology in 01.AI’s system came from Llama. Mr. Lee’s start-up then built on Meta’s technology, training its system with new data to make it more powerful. This assessment is based on a misreading of the cited Hugging Face issue. While we make no claims about the overall…

23 May

The Role of Synthetic Data in Cybersecurity

stp2y0 CommentsViral News

Data's value is something of a double-edged sword. On one hand, digital data lays the groundwork for powerful AI applications, many of which could change the world for the better. Conversely, storing so many details on people creates huge privacy risks. Synthetic data provides a possible solution. What Is Synthetic Data? Synthetic data is a subset of anonymized data – data that doesn't reveal any real-world details. More specifically, it refers to information that looks and acts like real-world data but has no ties to actual people, places or events. In short, it's fake data that can produce real results. In…

23 May

OpenAI will reportedly pay $250 million to put News Corp’s journalism in ChatGPT

stp2y0 CommentsNewsgear, generative ai, news, News Corp, openai, rupert murdoch, sam altman

OpenAI and News Corp, the owner of The Wall Street Journal, MarketWatch, The Sun, and more than a dozen other publishing brands, have struck a multi-year deal to display news from these publications in ChatGPT, News Corp announced on Wednesday. OpenAI will be able to access both current and well as archived content from News Corp’s publications and use the data to further train its AI models. Neither company disclosed the terms of the deal, but a report in The Wall Street Journal estimated that News Corp would get $250 million over five years in cash and credits.“The pact acknowledges…

23 May

The Low-Paid Humans Behind AI’s Smarts Ask Biden to Free Them From ‘Modern Day Slavery’

stp2y0 CommentsAIafrica, artificial intelligence, chatgpt, content moderation, crowdsourcing, joe biden, labor, meta, openai, social media

AI projects like OpenAI’s ChatGPT get part of their savvy from some of the lowest-paid workers in the tech industry—contractors often in poor countries paid small sums to correct chatbots and label images. On Wednesday, 97 African workers who do AI training work or online content moderation for companies like Meta and OpenAI published an open letter to President Biden, demanding that US tech companies stop “systemically abusing and exploiting African workers.”Most of the letter’s signatories are from Kenya, a hub for tech outsourcing, whose president, William Ruto, is visiting the US this week. The workers allege that the practices…

23 May

Webinar Replay – Space Loves AI: How AI promises to transform space operations

stp2y0 CommentsChat-GPT

For satellite operators, AI’s potential benefits are impossible to ignore. As Earth observation and communications constellations expand, AI tools promise to streamline operations, reduce on-orbit collisions and speed up analysis of remote sensing data. Opportunities and challenges for space-based AI with experts from the Aerospace Corporation, Stanford University’s Center for AEroSpace Autonomy Research (CAESAR), Magnestar, and Redwire Space were discussed. Panelists Mike Nemerouf, DirectorInnovation, Science and Technology Aerospace Corporation Al Tadros, CTORedwire Space Simone D’Amico, Co-founderStanford Center for AEroSpace Autonomy Research Moderator Debra WernerSenior Staff WriterSpaceNews Sponsored By Whether your mission requires persistent, high-resolution imagery or resilient communications, Redwire’s highly…

23 May

Building MLOps Capabilities at GitLab As a One-Person ML Platform Team

stp2y0 CommentsGenAI

Eduardo Bonet is an incubation engineer at GitLab, building out their MLOps capabilities. One of the first features Eduardo implemented in this role was a diff for Jupyter Notebooks, bringing code reviews into the data science process. Eduardo believes in an iterative, feedback-driven product development process, although he emphasizes that “minimum viable change” does not necessarily mean that there is an immediately visible value-add from the user’s point of view. While LLMs are quickly gaining traction, Eduardo thinks they’ll not replace ML or traditional software engineering but add to the capabilities. Thus, he believes that GitLab’s current focus on MLOps…

23 May

Generative AI Translation Startup DeepL Locks Up $300M

stp2y0 CommentsRAG models

Investors can’t get enough of different ways to use generative AI. Translation and language startup DeepL became the latest startup using generative AI to raise big, nabbing $300 million at a $2 billion post-money valuation in a round led by Index Ventures. The valuation is about double its previous $1 billion-plus valuation from January 2023. The round included participation from ICONIQ Growth, Teachers’ Venture Growth, IVP, Atomico and WiL (World Innovation Lab). The German startup language AI platform offers writing, editing and translation services for 63 markets and 32 languages for business use cases. The company said it has already…

22 May

Announcing General Availability of Liquid Clustering

stp2y0 CommentsViral Newsdata management, delta lake, liquid clustering

We’re excited to announce the General Availability of Delta Lake Liquid Clustering in the Databricks Data Intelligence Platform. Liquid Clustering is an innovative data management technique that replaces table partitioning and ZORDER so you no longer have to fine-tune your data layout to achieve optimal query performance. Liquid clustering significantly simplifies data layout-related decisions and provides the flexibility to redefine clustering keys without data rewrites. It allows data layout to evolve alongside analytic needs over time – something you could never do with partitioning on Delta. Since the Public Preview of Liquid Clustering at the Data and AI Summit last year, we’ve…

22 May

Beautiful dashboards in Python with first-class real-time integration | Deephaven

stp2y0 CommentsNews

from deephaven import ui, agg, empty_tablefrom deephaven.stream.table_publisher import table_publisherfrom deephaven.stream import blink_to_append_onlyfrom deephaven.plot import express as dxfrom deephaven import updateby as ubyfrom deephaven import dtypes as dhtstocks = dx.data.stocks().reverse()def set_bol_properties(fig): fig.update_layout(showlegend=False) fig.update_traces(fill="tonexty", fillcolor='rgba(255,165,0,0.08)')@ui.componentdef line_plot( filtered_source, exchange, window_size, bol_bands): window_size_key = { "5 seconds": ("priceAvg5s", "priceStd5s"), "30 seconds": ("priceAvg30s", "priceStd30s"), "1 minute": ("priceAvg1m", "priceStd1m"), "5 minutes": ("priceAvg5m", "priceStd5m")} bol_bands_key = {"None": None, "80%": 1.282, "90%": 1.645, "95%": 1.960, "99%": 2.576} base_plot = ui.use_memo(lambda: ( dx.line(filtered_source, x="timestamp", y="price", by="exchange" if exchange == "All" else None, unsafe_update_figure=lambda fig: fig.update_traces(opacity=0.4)) ), [filtered_source, exchange]) window_size_avg_key_col = window_size_key[window_size][0] window_size_std_key_col = window_size_key[window_size][1] avg_plot = ui.use_memo(lambda: dx.line(filtered_source, x="timestamp",…

22 May

Ghostbuster: Detecting Text Ghostwritten by Large Language Models

stp2y0 CommentsAIlarge language models, text generation

The structure of Ghostbuster, our new state-of-the-art method for detecting AI-generated text. Large language models like ChatGPT write impressively well—so well, in fact, that they’ve become a problem. Students have begun using these models to ghostwrite assignments, leading some schools to ban ChatGPT. In addition, these models are also prone to producing text with factual errors, so wary readers may want to know if generative AI tools have been used to ghostwrite news articles or other sources before trusting them. What can teachers and consumers do? Existing tools to detect AI-generated text sometimes do poorly on data that differs from…