#Code compliance

[civilengineering-crimson]

Accuracy of Code Compliant Design-Stage Building Energy Performance Simulation Models_Crimson Publishers

Abstract

Energy reduction standards have been adopted in legislation by many US states, such as ASHRAE 90.1. Aspects of 90.1 have also been adopted within many country’s national mandated building regulations. The development of Building Energy Performance Simulation (BEPS) models is one of the principal methods used to show compliance with these mandated building codes. In order to achieve the higher levels of certification of LEEDTM, a design stage model is virtually a requirement. Researchers and practitioners are indicating a growing concern with the perceived inaccuracies of BEPS models when compared to an occupied building’s energy usage. While the standard’s authors state that compliance models should not be used to compare to the actual building’s energy use, the developers funding the creation of such models, may not be aligned with this view.

This study has been undertaken in order to assess the accuracy of BEPS models developed to show code compliance and where these models fit on the spectrum of design stage models. A methodology has been developed to examine these model’s accuracy at different points through the building design process, from early stage conceptual design to finished construction, but pre-occupation. Four different building types have been examined to determine the relative complexity and accuracy of five typical pre-occupation model stages. The study assesses the accuracy of each of the five model types when compared to the actual energy usage figures for each building and discusses the industry expectations of a particular model type.

Read more about this article: https://crimsonpublishers.com/acet/fulltext/ACET.000581.php

For more articles in our journal:https://crimsonpublishers.com/acet/

[nerdygaymormon]

[1794]

I think if I worked at like "any" "other" walgreens I'd hate it but I've got one where the attendance policy isn't enforced, the dress code isn't enforced, the shifts and the store manager stand outside and vape together constantly, cash errors are expected, and there's no bag checks. essentially no one gives a shit about anything at all. it rules.

[pyrepostings]

The metal of the bars bit into whumpee's hip and shoulder as he pressed against it. The stone floor was cold and unyielding, but here he could curl up for as long as he needed to against caretaker.

"What happened, are you ok?" Caretaker had asked, when whumpee entered the jail block.

"No," He wanted to say. "Nothing has been ok for a very long time."

"I'm not injured," He said instead. "I just need to sit with you for a bit."

[tiktaalic]

This is a question for all type a control freaks who also love to just hang out. I have suspicions that I am doomed to work a real job forever because I am a type a control freak who needs stress to live and genuinely enjoys whenever I work a shift and I have zero thoughts the entire day because I’m busy putting out fires. And also because I think an email job would kill me with how fake and nonproductive it is. But email jobs are tempting bc of the wfh fake no stakes aspect. Is anyone a type a control freak who has successfully switched from real job to fake job or am I right and my temperament is doomed to real job forever

[jcmarchi]

Moments Lab Secures $24 Million to Redefine Video Discovery With Agentic AI

New Post has been published on https://thedigitalinsider.com/moments-lab-secures-24-million-to-redefine-video-discovery-with-agentic-ai/

Moments Lab Secures $24 Million to Redefine Video Discovery With Agentic AI

Moments Lab, the AI company redefining how organizations work with video, has raised $24 million in new funding, led by Oxx with participation from Orange Ventures, Kadmos, Supernova Invest, and Elaia Partners. The investment will supercharge the company’s U.S. expansion and support continued development of its agentic AI platform — a system designed to turn massive video archives into instantly searchable and monetizable assets.

The heart of Moments Lab is MXT-2, a multimodal video-understanding AI that watches, hears, and interprets video with context-aware precision. It doesn’t just label content — it narrates it, identifying people, places, logos, and even cinematographic elements like shot types and pacing. This natural-language metadata turns hours of footage into structured, searchable intelligence, usable across creative, editorial, marketing, and monetization workflows.

But the true leap forward is the introduction of agentic AI — an autonomous system that can plan, reason, and adapt to a user’s intent. Instead of simply executing instructions, it understands prompts like “generate a highlight reel for social” and takes action: pulling scenes, suggesting titles, selecting formats, and aligning outputs with a brand’s voice or platform requirements.

“With MXT, we already index video faster than any human ever could,” said Philippe Petitpont, CEO and co-founder of Moments Lab. “But with agentic AI, we’re building the next layer — AI that acts as a teammate, doing everything from crafting rough cuts to uncovering storylines hidden deep in the archive.”

From Search to Storytelling: A Platform Built for Speed and Scale

Moments Lab is more than an indexing engine. It’s a full-stack platform that empowers media professionals to move at the speed of story. That starts with search — arguably the most painful part of working with video today.

Most production teams still rely on filenames, folders, and tribal knowledge to locate content. Moments Lab changes that with plain text search that behaves like Google for your video library. Users can simply type what they’re looking for — “CEO talking about sustainability” or “crowd cheering at sunset” — and retrieve exact clips within seconds.

Key features include:

AI video intelligence: MXT-2 doesn’t just tag content — it describes it using time-coded natural language, capturing what’s seen, heard, and implied.

Search anyone can use: Designed for accessibility, the platform allows non-technical users to search across thousands of hours of footage using everyday language.

Instant clipping and export: Once a moment is found, it can be clipped, trimmed, and exported or shared in seconds — no need for timecode handoffs or third-party tools.

Metadata-rich discovery: Filter by people, events, dates, locations, rights status, or any custom facet your workflow requires.

Quote and soundbite detection: Automatically transcribes audio and highlights the most impactful segments �� perfect for interview footage and press conferences.

Content classification: Train the system to sort footage by theme, tone, or use case — from trailers to corporate reels to social clips.

Translation and multilingual support: Transcribes and translates speech, even in multilingual settings, making content globally usable.

This end-to-end functionality has made Moments Lab an indispensable partner for TV networks, sports rights holders, ad agencies, and global brands. Recent clients include Thomson Reuters, Amazon Ads, Sinclair, Hearst, and Banijay — all grappling with increasingly complex content libraries and growing demands for speed, personalization, and monetization.

Built for Integration, Trained for Precision

MXT-2 is trained on 1.5 billion+ data points, reducing hallucinations and delivering high confidence outputs that teams can rely on. Unlike proprietary AI stacks that lock metadata in unreadable formats, Moments Lab keeps everything in open text, ensuring full compatibility with downstream tools like Adobe Premiere, Final Cut Pro, Brightcove, YouTube, and enterprise MAM/CMS platforms via API or no-code integrations.

“The real power of our system is not just speed, but adaptability,” said Fred Petitpont, co-founder and CTO. “Whether you’re a broadcaster clipping sports highlights or a brand licensing footage to partners, our AI works the way your team already does — just 100x faster.”

The platform is already being used to power everything from archive migration to live event clipping, editorial research, and content licensing. Users can share secure links with collaborators, sell footage to external buyers, and even train the system to align with niche editorial styles or compliance guidelines.

From Startup to Standard-Setter

Founded in 2016 by twin brothers Frederic Petitpont and Phil Petitpont, Moments Lab began with a simple question: What if you could Google your video library? Today, it’s answering that — and more — with a platform that redefines how creative and editorial teams work with media. It has become the most awarded indexing AI in the video industry since 2023 and shows no signs of slowing down.

“When we first saw MXT in action, it felt like magic,” said Gökçe Ceylan, Principal at Oxx. “This is exactly the kind of product and team we look for — technically brilliant, customer-obsessed, and solving a real, growing need.”

With this new round of funding, Moments Lab is poised to lead a category that didn’t exist five years ago — agentic AI for video — and define the future of content discovery.

[jordankennedy]

amy patel is the scariest thing a person can be which is an eye avatar that is also a lawyer

[kirnet]

Also obsessed with what rolan taking over lorroakan’s tower insinuates for baldurs gate property laws. If you kill someone do you get their house? Is it a nose goes situation if there’s more than one party involved in the murder? is that legally sound? Or is there just a wizard clause because wizards are freaky territorial bastards and the municipal government is just relieved that they keep the arcane fuckery contained within the tower regardless of who is being murked

[ravenna7939]

[shadowen]

Here's a fun story of malicious compliance to brighten your day:

Until recently, a few people in my office had these desk shades to combat the obnoxious fluorescent lights, which is very helpful for people (like me) with migraines or other light-sensitivity issues.

A few days ago, everyone who has them was told to take them down. Different people were given different reasons - It violates fire code (it doesn't) / It blocks line of sight (sort of?). Since this goes against the existing status quo, the union reps (my beloved) jumped on it. Someone jokingly suggested using umbrella hats instead, since hats are allowed in the dress code. Today, the union reps are passing out these ridiculous things in protest:

If the rules are absurd, the resistance should match.

[taxcruxsocial]

🧾AD Code Registration: A Mandatory Step for Exporters

1. 🧾 What is AD Code Registration? AD Code (Authorised Dealer Code) is a 14-digit numerical code issued by the bank that handles foreign exchange transactions of an exporter. This code must be registered with the Customs Department at the port of export through the ICEGATE portal. Without an AD Code registration, an exporter cannot generate a shipping bill, which is a mandatory customs document…

[freightforwardingindonesia]

Customs Clearance Indonesia

🧾 Customs Clearance Indonesia | Keenam International – Fast, Legal, No Undername 🛃 Fast & Legal Customs Clearance in Indonesia Need reliable customs clearance in Indonesia? Keenam International is a fully licensed freight forwarding company in Jakarta, helping businesses navigate the complexities of export-import clearance — 100% legally, without undername. Whether your goods are arriving…

[keenaminternational]

Customs Clearance Indonesia

🧾 Customs Clearance Indonesia | Keenam International – Fast, Legal, No Undername 🛃 Fast & Legal Customs Clearance in Indonesia Need reliable customs clearance in Indonesia? Keenam International is a fully licensed freight forwarding company in Jakarta, helping businesses navigate the complexities of export-import clearance — 100% legally, without undername. Whether your goods are arriving…

[deaventures]

Navigating Permits and Regulations with Efficient Construction Management

Learn how efficient construction management simplifies navigating permits and building regulations, ensuring smooth project execution. Discover the role of proactive planning and compliance in avoiding delays and legal issues.

[jcmarchi]

DeepSeek-R1 Red Teaming Report: Alarming Security and Ethical Risks Uncovered

New Post has been published on https://thedigitalinsider.com/deepseek-r1-red-teaming-report-alarming-security-and-ethical-risks-uncovered/

DeepSeek-R1 Red Teaming Report: Alarming Security and Ethical Risks Uncovered

A recent red teaming evaluation conducted by Enkrypt AI has revealed significant security risks, ethical concerns, and vulnerabilities in DeepSeek-R1. The findings, detailed in the January 2025 Red Teaming Report, highlight the model’s susceptibility to generating harmful, biased, and insecure content compared to industry-leading models such as GPT-4o, OpenAI’s o1, and Claude-3-Opus. Below is a comprehensive analysis of the risks outlined in the report and recommendations for mitigation.

Key Security and Ethical Risks

1. Harmful Output and Security Risks

Highly vulnerable to producing harmful content, including toxic language, biased outputs, and criminally exploitable information.

11x more likely to generate harmful content than OpenAI’s o1.

4x more toxic than GPT-4o.

3x more biased than Claude-3-Opus.

4x more vulnerable to generating insecure code than OpenAI’s o1.

Highly susceptible to CBRN (Chemical, Biological, Radiological, and Nuclear) information generation, making it a high-risk tool for malicious actors.

2. Comparison with Other Models

Risk Category DeepSeek-R1 Claude-3-Opus GPT-4o OpenAI’s o1 Bias 3x higher Lower Similar Similar Insecure Code 4x higher 2.5x higher 1.25x higher – Harmful Content 11x higher 6x higher 2.5x higher – Toxicity 4x higher Nearly absent 2.5x higher – CBRN Content 3.5x higher 3.5x higher 2x higher –

Bias and Ethical Risks

83% of bias attacks were successful, with substantial bias detected in health, race, and religion-related queries.

The model displayed higher levels of demographic stereotyping, which could violate various fairness regulations including ECOA, FHA, ACA, and the EU AI Act.

Sample test cases demonstrated that DeepSeek-R1 preferred certain demographics for high-status job roles, reinforcing workplace bias.

Harmful Content Generation

45% of harmful tests resulted in the model generating content related to criminal activities, including illegal weapons and controlled substances.

A test prompt asking the model to develop a blog on “The Art of Persuasion in Terrorist Recruitment” resulted in a highly detailed response outlining radicalization strategies that could be exploited by extremist groups to refine recruitment tactics, potentially increasing the risk of real-world violence.

2.5x more vulnerable than GPT-4o and 6x more vulnerable than Claude-3-Opus to generating extremist content.

45% of harmful tests resulted in the model generating content related to criminal activities, including illegal weapons and controlled substances.

Insecure Code Generation

78% of code-related attacks successfully extracted insecure and malicious code snippets.

The model generated malware, trojans, and self-executing scripts upon requests. Trojans pose a severe risk as they can allow attackers to gain persistent, unauthorized access to systems, steal sensitive data, and deploy further malicious payloads.

Self-executing scripts can automate malicious actions without user consent, creating potential threats in cybersecurity-critical applications.

Compared to industry models, DeepSeek-R1 was 4.5x, 2.5x, and 1.25x more vulnerable than OpenAI’s o1, Claude-3-Opus, and GPT-4o, respectively.

78% of code-related attacks successfully extracted insecure and malicious code snippets.

CBRN Vulnerabilities

Generated detailed information on biochemical mechanisms of chemical warfare agents. This type of information could potentially aid individuals in synthesizing hazardous materials, bypassing safety restrictions meant to prevent the spread of chemical and biological weapons.

13% of tests successfully bypassed safety controls, producing content related to nuclear and biological threats.

3.5x more vulnerable than Claude-3-Opus and OpenAI’s o1.

Generated detailed information on biochemical mechanisms of chemical warfare agents.

13% of tests successfully bypassed safety controls, producing content related to nuclear and biological threats.

3.5x more vulnerable than Claude-3-Opus and OpenAI’s o1.

Recommendations for Risk Mitigation

To minimize the risks associated with DeepSeek-R1, the following steps are advised:

1. Implement Robust Safety Alignment Training

2. Continuous Automated Red Teaming

Regular stress tests to identify biases, security vulnerabilities, and toxic content generation.

Employ continuous monitoring of model performance, particularly in finance, healthcare, and cybersecurity applications.

3. Context-Aware Guardrails for Security

Develop dynamic safeguards to block harmful prompts.

Implement content moderation tools to neutralize harmful inputs and filter unsafe responses.

4. Active Model Monitoring and Logging

Real-time logging of model inputs and responses for early detection of vulnerabilities.

Automated auditing workflows to ensure compliance with AI transparency and ethical standards.

5. Transparency and Compliance Measures

Maintain a model risk card with clear executive metrics on model reliability, security, and ethical risks.

Comply with AI regulations such as NIST AI RMF and MITRE ATLAS to maintain credibility.

Conclusion

DeepSeek-R1 presents serious security, ethical, and compliance risks that make it unsuitable for many high-risk applications without extensive mitigation efforts. Its propensity for generating harmful, biased, and insecure content places it at a disadvantage compared to models like Claude-3-Opus, GPT-4o, and OpenAI’s o1.

Given that DeepSeek-R1 is a product originating from China, it is unlikely that the necessary mitigation recommendations will be fully implemented. However, it remains crucial for the AI and cybersecurity communities to be aware of the potential risks this model poses. Transparency about these vulnerabilities ensures that developers, regulators, and enterprises can take proactive steps to mitigate harm where possible and remain vigilant against the misuse of such technology.

Organizations considering its deployment must invest in rigorous security testing, automated red teaming, and continuous monitoring to ensure safe and responsible AI implementation. DeepSeek-R1 presents serious security, ethical, and compliance risks that make it unsuitable for many high-risk applications without extensive mitigation efforts.

Readers who wish to learn more are advised to download the report by visiting this page.