1. No one owes you anything. You are replaceable, but your unique talent and experience can make you irreplaceable.
2. Success is not about working smart, but about failure management. Fail often but fail fast.
3. Knowing how to communicate with others is more important than hard work.
4. Your education will only take you so far, experience is key.
5. Your attitude and mindset will determine your success more than your skills.
6. Luck plays a big role in success, but preparation increases your chances of luck.
7. Your competition is working harder than you think.
8. Your reputation is your most valuable asset.
9. Time management is crucial, prioritize wisely.
10. Personal growth is a never-ending journey, not a destination.
11. Your success is mostly determined by your ability to adapt to change.
12. Take calculated risks.
13. When all seems at end, give time to time.

https://www.reshot.ai/

https://www.linkedin.com/feed/update/urn:li:activity:7238850453638184961

local copy in the article:

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https://radiancefields.com/sony-pcl-shows-proprietary-nerfs-for-virtual-production

https://depthcrafter.github.io/

We innovate DepthCrafter, a novel video depth estimation approach, by leveraging video diffusion models. It can generate temporally consistent long depth sequences with fine-grained details for open-world videos, without requiring additional information such as camera poses or optical flow.

https://loopyavatar.github.io/

Loopy supports various visual and audio styles. It can generate vivid motion details from audio alone, such as non-speech movements like sighing, emotion-driven eyebrow and eye movements, and natural head movements.

For years, tech firms were fighting a war for talent. Now they are waging war on talent.

This shift has led to a weakening of the social contract between employees and employers, with culture and employee values being sidelined in favor of financial discipline and free cash flow.

The operating environment has changed from a high tolerance for failure (where cheap capital and willing spenders accepted slipped dates and feature lag) to a very low – if not zero – tolerance for failure (fiscal discipline is in vogue again).

While preventing and containing mistakes staves off shocks to the income statement, it doesn’t fundamentally reduce costs. Years of payroll bloat – aggressive hiring, aggressive comp packages to attract and retain people – make labor the biggest cost in tech.
…

Of course, companies can reduce their labor force through natural attrition. Other labor policy changes – return to office mandates, contraction of fringe benefits, reduction of job promotions, suspension of bonuses and comp freezes – encourage more people to exit voluntarily. It’s cheaper to let somebody self-select out than it is to lay them off.
…

Employees recruited in more recent years from outside the ranks of tech were given the expectation that we’ll teach you what you need to know, we want you to join because we value what you bring to the table. That is no longer applicable. Runway for individual growth is very short in zero-tolerance-for-failure operating conditions. Job preservation, at least in the short term for this cohort, comes from completing corporate training and acquiring professional certifications. Training through community or experience is not in the cards.
…

The ability to perform competently in multiple roles, the extra-curriculars, the self-directed enrichment, the ex-company leadership – all these things make no matter. The calculus is what you got paid versus how you performed on objective criteria relative to your cohort. Nothing more.
…

Here is where the change in the social contract is perhaps the most blatant. In the “destination employer” years, the employee invested in the community and its values, and the employer rewarded the loyalty of its employees through things like runway for growth (stretch roles and sponsored work innovation) and tolerance for error (valuing demonstrable learning over perfection in execution). No longer.
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http://www.rosspettit.com/2024/08/for-years-tech-was-fighting-war-for.html

With this technique you can train even with 12gb VRAM.

https://github.com/kijai/ComfyUI-FluxTrainer

https://www.visualcapitalist.com/eye-evolution/

A 2D Gaussian Splats technique for extracting cleaner 3D geometry from 3DGS

https://github.com/hbb1/2d-gaussian-splatting

https://surfsplatting.github.io/

https://colab.research.google.com/drive/1qoclD7HJ3-o0O1R8cvV3PxLhoDCMsH8W

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the multi-view inconsistent nature of 3D Gaussians. We present 2D Gaussian Splatting (2DGS), a novel approach to model and reconstruct geometrically accurate radiance fields from multi-view images. Our key idea is to collapse the 3D volume into a set of 2D oriented planar Gaussian disks. Unlike 3D Gaussians, 2D Gaussians provide view-consistent geometry while modeling surfaces intrinsically. To accurately recover thin surfaces and achieve stable optimization, we introduce a perspective-accurate 2D splatting process utilizing ray-splat intersection and rasterization. Additionally, we incorporate depth distortion and normal consistency terms to further enhance the quality of the reconstructions. We demonstrate that our differentiable renderer allows for noise-free and detailed geometry reconstruction while maintaining competitive appearance quality, fast training speed, and real-time rendering.

https://www.ilm.com/lighterdarker/s1e1-the-premiere/