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How the VFX industry is recovering from last year’s strikes
Jonathan Bronfman, CEO at MARZ, tells us: “I don’t think the industry will ever be the same. It will recover slowly in 2024. The streaming wars cost studios too much money and now they are all reevaluating their strategies.”
He notes that AI will play a big role in how things shake out. “Technology is pushing out the traditional approach, something which is long overdue. Studios in Hollywood have been operating the same way for decades, and now AI will move them off their pedestal.
“The entire industry is in for a reckoning. I think studios would have come to this realisation eventually, so it was inevitable, but I think the pressure from the strikes accelerated this.”
https://www.vfxwire.com/how-the-vfx-industry-is-recovering-from-last-years-strikes/
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Using Meta’s Llama 3 for your business
Meta is the only Big Tech company committed to developing AI, particularly large language models, with an open-source approach.
There are 3 ways you can use Llama 3 for your business:
1- Llama 3 as a Service
Use Llama 3 from any cloud provider as a service. You pay by use, but the price is typically much cheaper than proprietary models like GPT-4 or Claude.
→ Use Llama 3 on Azure AI catalog:
https://techcommunity.microsoft.com/t5/ai-machine-learning-blog/introducing-meta-llama-3-models-on-azure-ai-model-catalog/ba-p/41171442- Self-Hosting
If you have GPU infrastructure (on-premises or cloud), you can run Llama 3 internally at your desired scale.
→ Deploy Llama 3 on Amazon SageMaker:
https://www.philschmid.de/sagemaker-llama33- Desktop (Offline)
Tools like Ollama allow you to run the small model offline on consumer hardware like current MacBooks.
→ Tutorial for Mac:
https://ollama.com/blog/llama3 -
VES – How Generative AI Might Affect VFX Now and In the Future
Panelists include Author and Distinguished Research Scientist in DL/ML & CG at Wētā FX Dr. Andrew Glassner, VFX, Post & Technology Recruiter and VES 1st Vice Chair Susan O’Neal, CTO at Cinesite Group and VES Technology Committee member Michele Sciolette and Shareholder & Co-Chair of Buchalter’s Entertainment Industry Group and Adjunct Professor at Southwestern Law School Stephen Strauss, moderated by VES Technology Committee member and Media & Entertainment Executive, CTO & Industry Advisor Barbara Ford Grant.
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Is it possible to get a dark yellow
https://www.patreon.com/posts/102660674
https://www.linkedin.com/posts/stephenwestland_here-is-a-post-about-the-dark-yellow-problem-activity-7187131643764092929-7uCL
FEATURED POSTS
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The Perils of Technical Debt – Understanding Its Impact on Security, Usability, and Stability
In software development, “technical debt” is a term used to describe the accumulation of shortcuts, suboptimal solutions, and outdated code that occur as developers rush to meet deadlines or prioritize immediate goals over long-term maintainability. While this concept initially seems abstract, its consequences are concrete and can significantly affect the security, usability, and stability of software systems.
The Nature of Technical Debt
Technical debt arises when software engineers choose a less-than-ideal implementation in the interest of saving time or reducing upfront effort. Much like financial debt, these decisions come with an interest rate: over time, the cost of maintaining and updating the system increases, and more effort is required to fix problems that stem from earlier choices. In extreme cases, technical debt can slow development to a crawl, causing future updates or improvements to become far more difficult than they would have been with cleaner, more scalable code.
Impact on Security
One of the most significant threats posed by technical debt is the vulnerability it creates in terms of software security. Outdated code often lacks the latest security patches or is built on legacy systems that are no longer supported. Attackers can exploit these weaknesses, leading to data breaches, ransomware, or other forms of cybercrime. Furthermore, as systems grow more complex and the debt compounds, identifying and fixing vulnerabilities becomes increasingly challenging. Failing to address technical debt leaves an organization exposed to security risks that may only become apparent after a costly incident.
Impact on Usability
Technical debt also affects the user experience. Systems burdened by outdated code often become clunky and slow, leading to poor usability. Engineers may find themselves continuously patching minor issues rather than implementing larger, user-centric improvements. Over time, this results in a product that feels antiquated, is difficult to use, or lacks modern functionality. In a competitive market, poor usability can alienate users, causing a loss of confidence and driving them to alternative products or services.
Impact on Stability
Stability is another critical area impacted by technical debt. As developers add features or make updates to systems weighed down by previous quick fixes, they run the risk of introducing bugs or causing system crashes. The tangled, fragile nature of code laden with technical debt makes troubleshooting difficult and increases the likelihood of cascading failures. Over time, instability in the software can erode both the trust of users and the efficiency of the development team, as more resources are dedicated to resolving recurring issues rather than innovating or expanding the system’s capabilities.
The Long-Term Costs of Ignoring Technical Debt
While technical debt can provide short-term gains by speeding up initial development, the long-term costs are much higher. Unaddressed technical debt can lead to project delays, escalating maintenance costs, and an ever-widening gap between current code and modern best practices. The more technical debt accumulates, the harder and more expensive it becomes to address. For many companies, failing to pay down this debt eventually results in a critical juncture: either invest heavily in refactoring the codebase or face an expensive overhaul to rebuild from the ground up.
Conclusion
Technical debt is an unavoidable aspect of software development, but understanding its perils is essential for minimizing its impact on security, usability, and stability. By actively managing technical debt—whether through regular refactoring, code audits, or simply prioritizing long-term quality over short-term expedience—organizations can avoid the most dangerous consequences and ensure their software remains robust and reliable in an ever-changing technological landscape.
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Scientists claim to have discovered ‘new colour’ no one has seen before: Olo
https://www.bbc.com/news/articles/clyq0n3em41o
By stimulating specific cells in the retina, the participants claim to have witnessed a blue-green colour that scientists have called “olo”, but some experts have said the existence of a new colour is “open to argument”.
The findings, published in the journal Science Advances on Friday, have been described by the study’s co-author, Prof Ren Ng from the University of California, as “remarkable”.
(A) System inputs. (i) Retina map of 103 cone cells preclassified by spectral type (7). (ii) Target visual percept (here, a video of a child, see movie S1 at 1:04). (iii) Infrared cellular-scale imaging of the retina with 60-frames-per-second rolling shutter. Fixational eye movement is visible over the three frames shown.
(B) System outputs. (iv) Real-time per-cone target activation levels to reproduce the target percept, computed by: extracting eye motion from the input video relative to the retina map; identifying the spectral type of every cone in the field of view; computing the per-cone activation the target percept would have produced. (v) Intensities of visible-wavelength 488-nm laser microdoses at each cone required to achieve its target activation level.
(C) Infrared imaging and visible-wavelength stimulation are physically accomplished in a raster scan across the retinal region using AOSLO. By modulating the visible-wavelength beam’s intensity, the laser microdoses shown in (v) are delivered. Drawing adapted with permission [Harmening and Sincich (54)].
(D) Examples of target percepts with corresponding cone activations and laser microdoses, ranging from colored squares to complex imagery. Teal-striped regions represent the color “olo” of stimulating only M cones.