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Security Research on Private Cloud Compute

Apple is providing third-party auditors and security researchers early access to their Private Cloud Compute (PCC) resources.
Apple is expanding its Security Bounty program to include PCC and offering significant rewards for reporting security or privacy issues.
Apple has published the Private Cloud Compute Security Guide, detailing the architecture and security features of PCC.
Certain key components of PCC's source code are made available for deeper analysis under a limited-use license agreement.

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Hackernoon

366

Image Credit: Hackernoon

Implementing Edge Detection with Python and OpenCV: A Step-by-Step Guide

Edge detection is fundamental in computer vision, allowing us to identify object boundaries within images.
This tutorial demonstrates implementing edge detection using the Sobel operator and the Canny edge detector with Python and OpenCV.
A Flask web application is created to allow users to upload images and view the edge detection results.
The application is styled using Bootstrap for a better user experience.

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Marktechpost

331

Microsoft AI Releases OmniParser Model on HuggingFace: A Compact Screen Parsing Module that can Convert UI Screenshots into Structured Elements

Microsoft has released OmniParser, a vision-based screen parsing model on Hugging Face.
OmniParser aims to bridge the gaps in current screen parsing techniques by enabling sophisticated GUI understanding without relying on additional contextual data.
The model uses specialized components such as interactable region detection, icon description, and OCR to parse GUI elements purely from screenshots.
OmniParser improves parsing accuracy, demonstrates impressive performance benchmarks, and eliminates the need for underlying HTML or view hierarchies, making it a versatile tool for GUI automation.

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Nvidia

345

Image Credit: Nvidia

Healthcare Leaders Across India Bring NVIDIA NIM for Hindi Language to LLM Applications

Leading healthcare organizations and research institutions in India have leveraged NVIDIA NIM microservices and artificial intelligence to drive breakthrough medical research and build powerful medical applications.
NVIDIA NIM microservices, including the new Nemotron-4-Mini-Hindi 4B microservice, enable new AI applications and large natural language models to be built in Hindi.
The new AI model has the potential to dramatically improve healthcare accessibility by investing in AI models designed within the country through initiatives like the IndiaAI Mission.
The IIT Madras Brain Centre is advancing neuroscience research using AI to analyze vast petabyte-sized datasets, accelerating research that could lead to life-saving discoveries.
IIIT-Delhi researchers predict that AI-guided antimicrobial stewardship will be a key component of preventing the tens of millions of deaths that could be caused by antimicrobial resistance between 2025 and 2050.
Bionic, developed by 5C Network, detected pathologies in scans, such as lung lesions in X-rays or brain masses in MRIs, and provided actionable insights to support clinicians in decision-making.
Innoplexus, a member of the Nvidia Inception program, has built an AI-powered life sciences platform for drug discovery powered by NVIDIA NIM, including the AlphaFold2 NIM microservice.
Using NVIDIA NIM microservices, Innoplexus generates synthetic patient data to boost its AI models and performs virtual screenings of 5.8 million small molecules in less than eight hours — 10x faster than without NIM.
NVIDIA NIM microservices are available as part of the NVIDIA AI Enterprise software platform that enables the creation of smarter and more efficient healthcare facilities.
Global system integrators, including Infosys, TCS, Tech Mahindra, and Wipro, are collaborating with NVIDIA to help life sciences and healthcare companies leverage generative AI advancements.

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Medium

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Image Credit: Medium

17 Projects for Developers to Build AI Features 100x Faster ‍

17 projects have been compiled in this article to help developers build AI features faster.
Latitude LLM: A framework for creating AI prompts
LiveKit Agents: for building AI-driven server programs.
Julep: used to create multi-step tasks with decision-making abilities.
Open WebUI: customizable AI Assistant platform.
Micro Agent: used to mitigate problems of unreliable code generation.
GPT Crawler: helps create interactive docs that respond to chat.
Composio: used to automate real-world workflows.
Langflow: platform for building AI apps with composable building blocks.
OpenLLM: chat UI for an LLM server.
GPT Engineer: for the automatic generation of web apps.
Void: AI syntax editor.
Unsloth: used for fine-tuning AI models.
Khoj: a fast, accurate semantic search on top of your docs.
Prompt Tools: a tool for testing prompts across different models.

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Tech Republic

192

Troubleshooting Linux: An Admin’s Guide

If you’re an administrator of systems, no matter the platform, you know that it’s only a matter of time before you find yourself having to troubleshoot any given problem.
Linux provides a wide range of pre-installed or easily installable tools for troubleshooting various issues.
One of the helpful tools mentioned is 'top', which displays running processes and resource usage in real-time.
By using 'top', administrators can identify processes consuming excessive CPU or memory and take necessary actions.

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Marktechpost

192

CMU Researchers Release Pangea-7B: A Fully Open Multimodal Large Language Models MLLMs for 39 Languages

A team of CMU researchers has introduced PANGEA, a multilingual multimodal large language model (MLLM) designed to bridge linguistic and cultural gaps.
PANGEA is trained on a newly curated dataset, PANGEAINS, and outperforms existing models in multilingual scenarios.
The evaluation of PANGEA on PANGEABENCH shows significant improvements, especially in multilingual tasks.
The open-sourcing of PANGEAINS, PANGEABENCH, and PANGEA models promotes equity and accessibility across linguistic and cultural boundaries.

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TechCrunch

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Image Credit: TechCrunch

Socket lands a fresh $40M to scan software for security flaws

Socket, a startup that provides tools to detect security vulnerabilities in open source code, has raised $40 million to address software supply chain security.
The software supply chain has become precarious, with outdated open source components and the risk of software supply chain attacks.
Socket's solution is a scanner that detects malicious code and alerts developers when dependencies and packages are updated or added.
Socket's impressive list of backers and clients, along with its ability to catch harmful code missed by other tools, contribute to its success.

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Siliconangle

193

Image Credit: Siliconangle

Genmo introduces Mochi 1, an open-source text-to-video generation model

Genmo Inc. introduces Mochi 1, an open-source model for text-to-video generation.
Mochi 1 offers improvements in motion quality and adherence to user instructions.
Genmo raises $28.4 million in Series A funding to advance artificial general intelligence.
The full release of Mochi 1, supporting HD video generation, is planned before the end of the year.

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VentureBeat

179

AI video startup Genmo launches Mochi 1, an open source rival to Runway, Kling, and others

Genmo has released Mochi 1, an open-source software to generate high-quality videos from text prompts, which can be used to train AI models in robotics and autonomous systems.
Genmo claims that Mochi 1 outperforms Runway’s Gen-3 Alpha, Luma AI’s Dream Machine, Kuaishou’s Kling, Minimax’s Hailuo, and many others in terms of prompt adherence and motion quality.
Under the Apache 2.0 license, Mochi 1 offers users free access to cutting-edge video generation while Mochi 1 HD, a higher-definition version, is expected to launch in 2021.
Genmo’s co-founders aim to make cutting edge AI technology accessible, stating that “it’s really important to democratise this technology and put it in the hands of as many people as possible. That’s one reason we’re open sourcing it.”
The release of Mochi 1 previews several significant advancements in video generation, including high-fidelity motion, strong prompt adherence and precise control over characters, settings and actions in generated videos.
Genmo raised $28.4m in a Series A funding round for Mochi 1’s development, led by NEA and with backing from Essence VC, The House Fund, WndrCo, Gold House Ventures and Eastlink Capital Partners.
Mochi 1, which uses the Asymmetric Diffusion Transformer architecture, comprises the largest ever open-source video generation model, with ten billion parameters, that uses visual reasoning four times more than it uses text to generate a high-quality video.
Though there are limitations to the Mochi 1 preview version, Genmo plans to advance the software to include image-to-video synthesis capabilities, improve model controllability and offer even greater motion fidelity.
Mochi 1’s release offers researchers, developers and product teams new applications in advertising, education and entertainment as well as the ability to generate synthetic data for AI models in robotics and autonomous systems.
Genmo is investing heavily to improve motion quality compared with other models.
Genmo invites users to try Mochi 1 at genmo.ai/play.

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Hackaday

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Image Credit: Hackaday

Libre Space Foundation Aims to Improve Satellite Tech

The Libre Space Foundation (LSF) is working towards making space technology more open-sourced.
LSF collaborated with Ondsel to develop a satellite deploying mechanism using open source software.
The LSF designed the PICOBUS satellite launcher system that successfully deployed CubeSats in space.
LSF maintains a database of their open source space projects to democratize low Earth orbit.

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Marktechpost

Meta AI Releases LayerSkip: A Novel AI Approach to Accelerate Inference in Large Language Models (LLMs)

Meta AI has released LayerSkip, an innovative AI approach to accelerate inference in large language models (LLMs).
LayerSkip combines layer dropout and early exit loss during training to create different sub-models within the main model.
It introduces self-speculative decoding, where early predictions are validated and corrected using remaining layers of the model.
LayerSkip improves inference efficiency, reduces memory requirements, and achieves significant speed improvements across various tasks.

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Hackernoon

290

Image Credit: Hackernoon

Pretty Slow / Ugly Fast: How to Optimize your Code in 19 Different Ways

JavaScript, at its core, was architected with certain performance considerations in mind, but these considerations often get overshadowed by newer features designed for ease of use rather than efficiency.
It is especially important in JavaScript to find a balance between elegance and performance, as sometimes beauty can come at a cost.
This article explores 19 examples of TypeScript/JavaScript code patterns, comparing common, elegant approaches to their more optimized, but perhaps less attractive, counterparts.
The author used a structured performance testing framework to measure execution time and memory usage at varying scales, revealing when certain optimizations kick in and how different environments can influence results.
The article covers various topics such as string concatenation, array copying, looping over arrays, object property access, map usage, object cloning, and array filtering, among others.
Some surprising results were found, such as destructuring being faster than dot notation in a simple performance test. Also, the spread operator was faster than using Object.assign() for object cloning.
The article stresses the importance of testing performance trade-offs and not assuming that pretty code is always slower than ugly code.
The conclusion is that there is no clear winner between pretty but slow and ugly but fast. The choice depends on the specific use case and balancing the trade-offs between performance and readability.
Remember that the goal is to make more informed decisions when writing code, not to blindly assume that X is faster than Y. The only way to be 100% sure of your performance is to conduct your own tests.
If you're not running performance tests or measuring results, then you probably don't care about performance as much as you think.

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Hackaday

Image Credit: Hackaday

Open-Source, 3D Printed Trackpad

The Ploopy trackpad is an open-source 3D printed trackpad.
It features a 3D printed case and touch surface, with a Raspberry Pi Pico and QMK firmware.
Instructions for building the trackpad are available, as well as a Reddit thread for discussion.
Trackpads have evolved from basic types to high-quality devices, and this open-source option provides an alternative for DIY enthusiasts.

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The New Stack

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Image Credit: The New Stack

How Cloud Foundry Has Evolved With Kubernetes

The integration of Cloud Foundry and Kubernetes has expanded its capabilities.
In 2017, discussions began regarding the compatibility and integration of Cloud Foundry and K8s.
Projects like Fissile and SCF offered a more native approach to deploying CF on K8s.
KubeCF and Eirini enabling CF to run natively on K8s.
The community fully embraced Kubernetes with the release of cf-for-k8s 1.0.
The Korifi project envisions CF on Kubernetes that offers the same developer experience as CF.
The tech world is certainly big enough for the two technologies to co-exist.
Both Cloud Foundry and K8s assume applications are designed with 12-factor principles.
Cloud Foundry remains a powerful platform for managing large-scale, homogenous workloads.
Cloud Foundry will continue to exist as a well-maintained option for converged experience.

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