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Siliconangle

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Building AI with AI: Developers scramble to keep pace with new applications as security concerns grow

Generative artificial intelligence is reshaping software development, with developers utilizing AI for code building and creation of AI agents.
The demand for AI agents is impacting developers' work, advancing AI capabilities at a fast pace.
New applications for agentic AI are prompting companies like DigitalOcean to launch platforms like GenAI for AI agent building and deployment.
AI agents are being adopted in risk-averse sectors like financial services for tasks such as fraud detection and help desk inquiries.
Generative AI is influencing developer toolsets, with the introduction of open-source frameworks like Goose to simplify AI agent creation.
Security concerns arise regarding building agents from large language models, with malware distribution risks being highlighted.
Checkmarx CEO Sandeep Johri emphasizes the importance of thorough code scanning due to potential hacker exploits in AI-generated code.
Developers acknowledge the need for human involvement alongside AI agents to ensure compliance with specifications.
The future entails AI systems becoming companions for developers, with human supervision remaining crucial for oversight.
The dynamic AI landscape necessitates a balance between AI capabilities and human oversight to address security risks and ensure proper behavior.

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Medium

335

Image Credit: Medium

Beathoven.ai,

Beatoven.ai is an AI-powered tool that turns prompts into royalty-free background music.
It is perfect for non-developers and can be seamlessly integrated with Expo for app development.
Browser Use Cloud is an open-source tool that saves time and manual work for developers.
These tools are game-changers for creators, developers, and automation enthusiasts.

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Medium

349

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Cross-Site Scripting (XSS) 101

XSS (Cross-Site Scripting) continues to be a significant security vulnerability.
Websites often fail to properly sanitize user input, leading to potential XSS attacks.
XSS vulnerabilities can be found in server-side code, database storage, and in the browser's DOM.
Sanitizing user inputs is crucial to prevent XSS vulnerabilities.

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Marktechpost

277

NuminaMath 1.5: Second Iteration of NuminaMath Advancing AI-Powered Mathematical Problem Solving with Enhanced Competition-Level Datasets, Verified Metadata, and Improved Reasoning Capabilities

Project-Numina has launched NuminaMath 1.5, an advanced AI training dataset for mathematical reasoning.
NuminaMath 1.5 offers approximately 900,000 competition-level mathematical problems with structured Chain of Thought (CoT) methodology.
The dataset includes enriched problem metadata, such as final answers, mathematical domains, and problem types.
NuminaMath 1.5 focuses on curated and verified data, removing synthetic problems and ensuring high-quality resources for AI training.

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Softwareengineeringdaily

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LangChain and Agentic AI Engineering with Erick Friis

LangChain is an open-source framework used for building AI-driven applications.
Erick Friis, the Founding Engineer at LangChain, discusses the creation of LangChain and agentic AI design.
LangChain is commonly used for chatbots, question-answering systems, and workflow automation.
The podcast episode covers topics such as agentic flows vs. chained flows and emerging patterns in agentic AI design.

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Hackernoon

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Image Credit: Hackernoon

This Library Translates Confusing FHIR Dosage Data Into Actual Human Words

This library is designed to translate confusing FHIR dosage data into actual human words.
It is compatible with Dosage R4 and R5 and can be easily integrated into different systems.
The library is extensible, allowing developers to customize it according to their needs.
It is internationalized with multilingual support, making it suitable for healthcare systems across different regions.

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Marktechpost

231

Zyphra Introduces the Beta Release of Zonos: A Highly Expressive TTS Model with High Fidelity Voice Cloning

Zyphra has introduced the beta release of Zonos-v0.1, a highly expressive text-to-speech (TTS) model with high-fidelity voice cloning.
The release includes a 1.6 billion-parameter transformer model and a similarly sized hybrid model. These models are trained on a large dataset encompassing various languages and offer controls over parameters such as speaking rate, pitch variation, and emotions.
Zonos-v0.1 features zero-shot TTS with voice cloning, audio prefix inputs, multilingual support, audio quality and emotion control, efficient performance, user-friendly interface, and straightforward deployment.
The models are optimized for real-time applications and can be easily integrated into existing workflows. Zyphra's Zonos-v0.1 represents a significant advancement in open-source TTS development.

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Silicon

272

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Macron Shares Deepfakes As AI Summit Begins

French president Emmanuel Macron shares deepfake videos of himself on social media as the AI summit begins in Paris.
France will announce private sector investments totaling €109 billion into the country's AI sector during the event.
Investments include €20 billion from Canadian investment firm Brookfield for an AI data center.
Macron promotes the importance of AI and its potential to revolutionize industries while emphasizing the need to promote principles and seize opportunities.

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Pyimagesearch

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Image Credit: Pyimagesearch

Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API

In this tutorial, we will learn how to build an engaging Gradio chatbot powered by Llama 3.2 and Ollama.
Gradio is an open-source Python library that enables developers to create user-friendly and interactive web applications effortlessly.
Ollama is an open-source framework that enables developers to run large language models (LLMs) like Llama 3.2 Vision locally on their machines.
Llama 3.2 represents a significant advancement in large language models (LLMs), introducing multimodal capabilities that enable the processing of both text and images.
The app.py script is the driver of the multimodal chatbot application. It integrates the Chatbot class from chatbot.py with the Gradio Blocks interface to provide an interactive user interface.
To follow this guide, you need to have the following Python packages installed: ollama==0.3.3, pillow==11.0.0 (PIL), and gradio==5.5.0.
The code is modularized across three key files: utils.py, chatbot.py, and app.py. Each file has a specific purpose, making the implementation extensible and easy to understand.
The result was a sophisticated chatbot capable of generating detailed, concise, or creative responses based on user preferences while maintaining conversation history.
This project showcased the seamless integration of Gradio, Llama 3.2 Vision, and Ollama’s API, offering developers a practical framework for creating advanced multimodal AI applications.
In conclusion, this tutorial explains how to build deep learning chatbot with practical examples and detailed walkthrough.

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Siliconangle

318

Image Credit: Siliconangle

Sam Altman pledges more openness as OpenAI works towards AGI

OpenAI CEO, Sam Altman, has claimed that his company intends to broadly distribute the benefits of achieving artificial general intelligence, giving everyone a “compute budget”. Altman has sought “early intervention” to ensure that the balance of power between capital and labour does not become too disrupted. OpenAI may be in talks over a $40bn funding round, just months after raising $6.6bn. Altman believes cheap access to the technology will increase as AI technology gains increases, and it becomes increasingly accessed by everyone, with millions of hyperscale AI systems that can tackle problems 'in every field of knowledge work'.
Altman has assured that he does not believe AGI-level systems will be the ones providing the biggest new ideas, but that he expects such systems to greatly enhance human innovation as they allow people to leverage artificial general intelligence to fulfil their goals and expand creativity. He also confirmed that the company would make major decisions to maintain safety if and when it creates an AGI-level system.
Many of the systems created by OpenAI have been kept under wraps so far and it now seems that the company will be adopting some open-source processes in a bid to be more open about its AI systems.
OpenAI plans to prevent AGI systems from being used by authoritarian governments to “control their population through mass surveillance” and forestall the “loss of autonomy”.
Altman’s plan for the company will be focused primarily on individual empowerment as it works to achieve the near-total distribution of the benefits of artificial general intelligence, Altman added.
OpenAI no longer sees its path as being purely not-for-profit, as it now aims to keep over $100bn in annual revenue by 2029.
The rise of Chinese AI outfit DeepSeek Limited indicates that powerful AI being developed may become more affordable in the future, though Altman reiterated that investments will need to be huge in order to achieve AGI.
Although an AGI-level system may cause job losses in certain sectors, its real value will be in running such systems at enormous scales and distributing broad benefits across society.
OpenAI's effort to democratise AGI makes it likely that the company will have to adopt a more open and transparent approach about AI technology. Altman has set a tone that will help OpenAI meet its current AI research demands.
Altman envisions a future in which AI manages problems “in every field of knowledge work”. Although the development of such ideas is still in the early stages, and many unproven and experimental theories are being tried every day, it is possible that OpenAI may become one of the leaders of AGI research in the future.

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Siliconangle

305

Image Credit: Siliconangle

Sam Altman pledges more openness as OpenAI works toward AGI

Sam Altman, the CEO of OpenAI, has set out his plans for ensuring everyone on the planet has access to artificial general intelligence (AGI) to nurture creative resources. Part of the plan is to give everyone a “compute budget”, an investment in something like cryptocurrency that will rise in value, to distribute the benefits of AGI across the globe. Altman believes such systems will need millions of hyperscale AI structures that can tackle every field of knowledge work but warns the costs are huge, even though the cost of using them falls around 10 times with each 12-month period.
OpenAI is already in talks to raise $40bn after it received $6.6bn. Altman said OpenAI plans to change its mission from the original aims of being non-profit to a for-profit company that hopes to achieve $100bn in annual revenues by 2029.
As OpenAI moves rapidly towards AGI-level systems, Altman said difficult decisions will have to be made on safety, which will include some unpopular limitations. This will have to include more openness about OpenAI’s AI systems despite the group being described as historically being “on the wrong side of history” in terms of open-source sharing.
Wider use of AGI-based systems could benefit society and boost the economy, but there are concerns that their introduction could also cause mass unemployment. Such systems require not only deployment at scale, but also heavy investment to ensure safety and development.
The historical progress of technological advancement has proven that most health and economic metrics get better in the long-term, but there is no proof that equality will be included in this progress, Altman pointed out. Capital could quickly become more powerful than labour, he warned.
AGI is defined by Altman as being 'a system that can tackle increasingly complex problems, at human level, in many fields.' He indicated that we are very close to achieving it, but also stressed the role of human supervision and guidance to avoid any possible disruption.
Once AGI systems are launched at an enormous scale, the value will be realised, according to Altman. Such systems will need heavy sums of investment, however, which is why OpenAI is reportedly talking to investors about raising another $40bn (three months after raising $6.6bn).
OpenAI has partnered with firms like Oracle to provide $500bn on data centres through President Trump’s Project Stargate. Altman expects the systems used by large and powerful AI structures to be great at certain things, but bad at others. As such, AI should be used to help individual members of society attain greater power rather than cradle authoritarian control.
Altman said that adopting an approach focussed on helping individuals will almost certainly result in the firm having to be more open about its AI systems.
Chinese AI startup DeepSeek, among others, supports the argument that developing and training powerful AI systems may become more affordable. However, Altman warns that heavy investment is necessary to achieve AGI.

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Marktechpost

Kyutai Releases Hibiki: A 2.7B Real-Time Speech-to-Speech and Speech-to-Text Translation with Near-Human Quality and Voice Transfer

Kyutai has developed Hibiki, a 2.7 billion-parameter decoder-only model for real-time speech-to-speech and speech-to-text translation.
Hibiki operates at a 12.5Hz framerate with a 2.2kbps bitrate and supports French-to-English translation while preserving voice characteristics.
The model employs contextual alignment and a neural audio codec for efficient translation generation and dynamic adjustment of translation delays.
Hibiki demonstrates strong performance in translation quality, speaker fidelity, and maintains a competitive latency, offering practical benefits for real-time speech translation.

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Hackaday

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Image Credit: Hackaday

Software in Progress

Open source software is in a constant state of development, with bugs being worked on in public.
While some open-source projects like Inkscape or Blender are more mature, the majority are still in progress.
Users with the expectation of finished software may become frustrated with the ongoing development process.
Contributing to open-source projects and helping with bug-hunting is essential for their growth and improvement.

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Medium

136

Signal: A Privacy-Friendly choice!

Signal is primarily funded by donations, with a significant portion coming from Brian Acton.
Signal is diversifying its revenue through user donations and other funding sources.
Signal's design limits the data it can provide, making it different from other U.S. tech companies.
Signal retains significantly less metadata compared to other messaging apps.

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8 Likes

Medium

410

Image Credit: Medium

3 free alternatives to OpenAI’s Operator that you can’t afford to miss

Browser-Use: An open-source library for building AI agents that interact with browsers.
Self-Operating Computer: A framework for connecting to LLMs and using voice commands to trigger workflows.
HyperBrowser: A Python library for building intelligent agents that interact with browsers programmatically.
These three free alternatives to OpenAI's Operator can help developers build their own browser agents.

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