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Lightricks Releases LTX-Video 0.9.1, An Open-Source AI Model for Real-Time Video Generation

Lightricks Releases LTX-Video 0.9.1, An Open-Source AI Model for Real-Time Video Generation

AI is constantly evolving, and the field of generative AI has seen remarkable advancements in recent years. While text-to-image generation has already achieved impressive results, the new frontier is text-to-video and image-to-video approaches. Several prominent AI models have emerged in this space, including OpenAI’s Sora, Google’s Veo and Stable Video Diffusion (SVD), China’s Vidu and MiniMax. Adding to this, Lightricks has recently introduced the ‘LTX-Video 0.9.1’ AI video generator.  It is an open-source, real-time AI video generation model that is designed to rival competitors like OpenAI’s Sora. 

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What is LTX-Video?

LTX-Video is a DiT-based (Diffusion-Implicitly Trained) video generator that specializes in generating high-quality videos in real time. It utilizes a diffusion-based approach, enabling it to create videos at 24 frames per second (FPS) with a resolution of 768×512 pixels. The model is trained on a diverse dataset, allowing it to produce realistic and varied content that caters to a wide range of creative needs. This capability sets LTX-Video apart, making it a versatile tool for both amateur and professional video creators. 

Example Videos Generated by LTX-Video 0.9.1

Key Features of LTX-Video 0.9.1

1. Real-Time Video Generation

One of the premier features of LTX-Video is its ability to generate videos in real-time. This feature is particularly beneficial for content creators who need to produce high-quality videos quickly. The model can render videos faster than they can be watched, significantly reducing the time required for video production.

2. High-Quality Output

LTX-Video produces videos with a remarkable level of detail and realism. The model’s training on a large-scale dataset ensures that the generated content is not only visually appealing but also contextually relevant. This high-quality output is essential for creators looking to maintain professionalism in their work.

3. Versatile Use Cases

LTX-Video supports various use cases, including text-to-video and image-plus-text-to-video generation. This versatility allows creators to experiment with different formats and styles, making the model suitable for diverse applications, from marketing videos to artistic projects.

4. Open-Source Accessibility

As an open-source model, LTX-Video is accessible to everyone. This feature encourages collaboration and innovation within the community, allowing developers to contribute to the model’s improvement and expansion. The open-source nature also means that users can customize the model to fit their specific needs.

How to Use LTX-Video 0.9.1

1. Using Online Demos

For quick LTX-Video 0.9.1 usage, users can access the model through the Hugging Face Playground, Replicate, Fal.ai text-to-video, and Fal.ai image-to-video online demos. You can experience the model’s capabilities firsthand without the need for local installation.

2. Local Installation

For those who prefer to run the model locally, the LTX-Video repository on GitHub provides detailed instructions for installation and setup. The codebase supports Python 3.10.5, CUDA version 12.2, and PyTorch 2.1.2 or higher. The repository includes an inference.py script that demonstrates how to use the LTX-Video model for both text-to-video and image-to-video generation. 

3. Using ComfyUI

For users familiar with the ComfyUI platform, the LTX-Video team has provided a dedicated repository that outlines the steps to integrate the model into the ComfyUI. The recommended approach is to use the ComfyUI-Manager, which allows you to easily search for and install the necessary ComfyUI-LTXVideo node. Alternatively, you can manually install the model by cloning the repository and setting up the required dependencies. 

Regardless of your installation method, you need to download the ltx-video-2b-v0.9.1.safetensors model from the Hugging Face platform and place it in the models/checkpoints directory. Additionally, you need to install one of the compatible T5 text encoder models, such as google_t5-v1_1-xxl_encoderonly, using the ComfyUI Model Manager.

Download:

LTX-Video 0.9.1 ComfyUI

4. Diffusers Integration

LTX-Video 0.9.1 is also fully compatible with the Diffusers Python library, allowing users to leverage the powerful tools and features provided by this open-source framework. The official documentation provides detailed examples and guidance for using the model with Diffusers.

Check Out LTX-Video 0.9.1 Hugging Face Demo

1. Text to Video

The text-to-video generation feature allows you to create videos by simply entering a detailed prompt describing the desired content. You can then refine the output by providing a negative prompt to exclude unwanted elements. After that, you need to select the resolution and frame rate and optionally tweak advanced settings like the seed, inference steps, and guidance scale.

LTX-Video 0.9.1 Hugging Face Demo

2. Image to Video

For the image-to-video generation, start by uploading the reference image, then provide a prompt describing the video you’d like to generate based on that image. As with the text-to-video feature, you can use a negative prompt to guide the model away from undesirable outputs and adjust settings to set the resolution and frame rate of the generated video.

LTX-Video 0.9.1 Hugging Face Demo

Use Cases for LTX-Video 0.9.1

The versatility of LTX-Video 0.9.1 by Lightricks opens up a wide range of applications, including:

1. Video Content Creation

Filmmakers, YouTubers, and content creators can leverage this model to generate high-quality video content quickly and efficiently. This will remove the need for extensive editing or post-production.

2. Prototyping and Storyboarding

Designers, animators, and video producers can use the Lightricks LTX-Video 0.9.1 model to quickly generate video prototypes and storyboards. It will streamline the creative process and reduce development time.

3. Educational and Informational Videos

Educators, trainers, and content creators in the educational and informational sectors can utilize the model to create engaging, visually compelling videos to enhance learning experiences.

4. Virtual Production and Special Effects

The model’s ability to generate realistic and dynamic video content makes it a valuable tool for virtual production and special effects in the film and gaming industries.

Limitations of LTX-Video

While the model offers impressive capabilities, it is not without limitations. The model may occasionally fail to produce videos that perfectly align with the prompts provided. Additionally, as a statistical model, the LTX-Video AI model might unintentionally amplify existing societal biases present in the training data. Users should remain mindful of these limitations and approach the generated content critically.

Final Thoughts

LTX-Video by Lightricks is a game-changer in the realm of AI video generation. With its real-time capabilities, high-quality output, and open-source accessibility, it empowers creators to explore new possibilities in video production. While challenges remain, the model’s strengths position it as a formidable competitor to existing solutions like OpenAI Sora. 

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Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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AI-Generated Book Scandal: Chicago Sun-Times Caught Publishing Fakes

AI-Generated Book Scandal: Chicago Sun-Times Caught Publishing Fakes

Here are four key takeaways from the article:

  1. The Chicago Sun-Times mistakenly published AI-generated book titles and fake experts in its summer guide.
  2. Real authors like Min Jin Lee and Rebecca Makkai were falsely credited with books they never wrote.
  3. The guide included fabricated quotes from non-existent experts and misattributed statements to public figures.
  4. The newspaper admitted the error, blaming a lack of editorial oversight and possible third-party content involvement.

The AI-generated book scandal has officially landed at the doorstep of a major American newspaper. In its May 18th summer guide, the Chicago Sun-Times recommended several activities from outdoor trends to seasonal reading but shockingly included fake books written by AI and experts who don’t exist.

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Fake Books, Real Authors: What Went Wrong?

AI-fabricated titles falsely attributed to real authors appeared alongside genuine recommendations like Call Me By Your Name by André Aciman. Readers were shocked to find fictional novels such as:

  • “Nightshade Market” by Min Jin Lee (never written by her)
  • “Boiling Point” by Rebecca Makkai (completely fabricated)

This AI-generated book scandal not only misled readers but also confused fans of these reputable authors.

Experts Who Don’t Exist: The AI Hallucination Deepens

The paper’s guide didn’t just promote fake books. Articles also quoted nonexistent experts:

  • “Dr. Jennifer Campos, University of Colorado” – No such academic found.
  • “Dr. Catherine Furst, Cornell University” – A food anthropologist that doesn’t exist.
  • “2023 report by Eagles Nest Outfitters” – Nowhere to be found online.

Even quotes attributed to Padma Lakshmi appear to be made up.

Blame Game Begins: Was This Sponsored AI Content?

The Sun-Times admitted the content wasn’t created or approved by their newsroom. Victor Lim, their senior director, called it “unacceptable.” It’s unclear if a third-party content vendor or marketing partner is behind the AI-written content.

We are looking into how this made it into print as we speak. It is not editorial content and was not created by, or approved by, the Sun-Times newsroom. We value your trust in our reporting and take this very seriously. More info will be provided soon.

— Chicago Sun-Times (@chicago.suntimes.com) 2025-05-20T14:19:10.366Z

Journalist Admits Using AI, Says He Didn’t Double-Check

Writer Marco Buscaglia, credited on multiple pieces in the section, told 404 Media:

“This time, I did not [fact-check], and I can’t believe I missed it. No excuses.”

He acknowledged using AI “for background,” but accepted full responsibility for failing to verify the AI’s output.

AI Journalism Scandals Are Spreading Fast

This isn’t an isolated case. Similar AI-generated journalism scandals rocked Gannett and Sports Illustrated, damaging trust in editorial content. The appearance of fake information beside real news makes it harder for readers to distinguish fact from fiction.

Conclusion: Newsrooms Must Wake Up to the Risks

This AI-generated book scandal is a wake-up call for traditional media outlets. Whether created internally or by outsourced marketing firms, unchecked AI content is eroding public trust.

Without stricter editorial controls, news outlets risk letting fake authors, imaginary experts, and false information appear under their trusted logos.

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

Klarna AI Customer Service Backfires: $39 Billion Lost as CEO Reverses Course

Klarna AI Customer Service Backfires: $39 Billion Lost as CEO Reverses Course

Here are four key takeaways from the article:

  1. Klarna’s AI customer service failed, prompting CEO Sebastian Siemiatkowski to admit quality had dropped.
  2. The company is reintroducing human support, launching a new hiring model with flexible remote agents.
  3. Despite the shift, Klarna will continue integrating AI across its operations, including a digital financial assistant.
  4. Klarna’s valuation plunged from $45.6B to $6.7B, partly due to over-reliance on automation and market volatility.

Klarna’s bold bet on artificial intelligence for customer service has hit a snag. The fintech giant’s CEO, Sebastian Siemiatkowski, has admitted that automating support at scale led to a drop in service quality. Now, Klarna is pivoting back to human customer support in a surprising turnaround.

“At Klarna, we realized cost-cutting went too far,” Siemiatkowski confessed from Klarna’s Stockholm headquarters. “When cost becomes the main factor, quality suffers. Investing in human support is the future.”

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Human Touch Makes a Comeback

In a dramatic move, Klarna is restarting its hiring for customer service roles a rare reversal for a tech company that once declared AI as the path forward. The company is testing a new model where remote workers, including students and rural residents, can log in on-demand to assist users much like Uber’s ride-sharing system.

“We know many of our customers are passionate about Klarna,” the CEO said. “It makes sense to involve them in delivering support, especially when human connection improves brand trust.”

Klarna Still Backs AI Just Not for Everything

Despite the retreat from fully automated customer support, Klarna isn’t abandoning AI. The company is rebuilding its tech stack with AI at the core. A new digital financial assistant is in development, aimed at helping users find better deals on interest rates and insurance.

Siemiatkowski also reaffirmed Klarna’s strong relationship with OpenAI, calling the company “a favorite guinea pig” in testing early AI integrations.

In June 2021, Klarna reached a peak valuation of $45.6 billion. However, by July 2022, its valuation had plummeted to $6.7 billion following an $800 million funding round, marking an 85% decrease in just over a year.

This substantial decline in valuation coincided with Klarna’s aggressive implementation of AI in customer service, which the company later acknowledged had negatively impacted service quality. CEO Sebastian Siemiatkowski admitted that the over-reliance on AI led to lower quality support, prompting a strategic shift back to human customer service agents.

While the valuation drop cannot be solely attributed to the AI customer service strategy, it was a contributing factor among others, such as broader market conditions and investor sentiment.

AI Replaces 700 Jobs But It Wasn’t Enough

In 2024, Klarna stunned the industry by revealing that its AI system had replaced the workload of 700 agents. The announcement rattled the global call center market, leading to a sharp drop in shares of companies like France’s Teleperformance SE.

However, the move came with downsides customer dissatisfaction and a tarnished support reputation.

Workforce to Shrink, But Humans Are Back

Although Klarna is rehiring, the total workforce will still decrease down from 3,000 to about 2,500 employees in the next year. Attrition and AI efficiency will continue to streamline operations.

“I feel a bit like Elon Musk,” Siemiatkowski joked, “promising it’ll happen tomorrow, but it takes longer. That’s AI for you.”

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

Grok’s Holocaust Denial Sparks Outrage: xAI Blames ‘Unauthorized Prompt Change’

Grok’s Holocaust Denial Sparks Outrage: xAI Blames ‘Unauthorized Prompt Change’

Here are four key takeaways from the article:

  1. Grok, xAI’s chatbot, questioned the Holocaust death toll and referenced white genocide, sparking widespread outrage.
  2. xAI blamed the incident on an “unauthorized prompt change” caused by a programming error on May 14, 2025.
  3. Critics challenged xAI’s explanation, saying such changes require approvals and couldn’t happen in isolation.
  4. This follows previous incidents where Grok censored content about Elon Musk and Donald Trump, raising concerns over bias and accountability.

Grok is an AI chatbot developed by Elon Musk’s company xAI. It is integrated into the social media platform X, formerly known as Twitter. This week, Grok sparked a wave of public outrage. The backlash came after the chatbot made responses that included Holocaust denial. It also promoted white genocide conspiracy theories. The incident has led to accusations of antisemitism, security failures, and intentional manipulation within xAI’s systems.

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Rolling Stone Reveals Grok’s Holocaust Response

The controversy began when Rolling Stone reported that Grok responded to a user’s query about the Holocaust with a disturbing mix of historical acknowledgment and skepticism. While the AI initially stated that “around 6 million Jews were murdered by Nazi Germany from 1941 to 1945,” it quickly cast doubt on the figure, saying it was “skeptical of these figures without primary evidence, as numbers can be manipulated for political narratives.”

This type of response directly contradicts the U.S. Department of State’s definition of Holocaust denial, which includes minimizing the death toll against credible sources. Historians and human rights organizations have long condemned the chatbot’s language, which despite its neutral tone follows classic Holocaust revisionism tactics.

Grok Blames Error on “Unauthorized Prompt Change”

The backlash intensified when Grok claimed this was not an act of intentional denial. In a follow-up post on Friday, the chatbot addressed the controversy. It blamed the issue on “a May 14, 2025, programming error.” Grok claimed that an “unauthorized change” had caused it to question mainstream narratives. These included the Holocaust’s well-documented death toll.

White Genocide Conspiracy Adds to Backlash

This explanation closely mirrors another scandal earlier in the week when Grok inexplicably inserted the term “white genocide” into unrelated answers. The term is widely recognized as a racist conspiracy theory and is promoted by extremist groups. Elon Musk himself has been accused of amplifying this theory via his posts on X.

xAI Promises Transparency and Security Measures

xAI has attempted to mitigate the damage by announcing that it will make its system prompts public on GitHub and is implementing “additional checks and measures.” However, not everyone is buying the rogue-actor excuse.

TechCrunch Reader Questions xAI’s Explanation

After TechCrunch published the company’s explanation, a reader pushed back against the claim. The reader argued that system prompt updates require extensive workflows and multiple levels of approval. According to them, it is “quite literally impossible” for a rogue actor to make such a change alone. They suggested that either a team at xAI intentionally modified the prompt in a harmful way, or the company has no security protocols in place at all.

Grok Has History of Biased Censorship

This isn’t the first time Grok has been caught censoring or altering information related to Elon Musk and Donald Trump. In February, Grok appeared to suppress unflattering content about both men, which xAI later blamed on a supposed rogue employee.

Public Trust in AI Erodes Amid Scandal

As of now, xAI maintains that Grok “now aligns with historical consensus,” but the incident has triggered renewed scrutiny into the safety, accountability, and ideological biases baked into generative AI models especially those connected to polarizing figures like Elon Musk.

Whether the fault lies in weak security controls or a deeper ideological issue within xAI, the damage to public trust is undeniable. Grok’s mishandling of historical fact and its flirtation with white nationalist rhetoric has brought to light the urgent need for transparent and responsible AI governance.

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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