Unboxing the Tenstorrent Grayskull AI Accelerator
Are you ready to take your AI and machine learning projects to the next level? Then look no further than the Tenstorrent Grayskull AI Accelerator. This powerful piece of technology is designed to accelerate deep learning workloads, providing you with the speed and efficiency needed to tackle even the most challenging tasks.
What’s in the Box
Let’s take a look at what comes in the box when you purchase the Tenstorrent Grayskull AI Accelerator:
- Grayskull AI Accelerator unit
- Power cable
- Quick start guide
- Customizable cooling solution
Setting Up
Once you have unboxed the Tenstorrent Grayskull AI Accelerator, it’s time to set it up. Follow these simple steps to get started:
- Connect the power cable to the unit and plug it into a power outlet.
- Install the customizable cooling solution to ensure optimal performance.
- Refer to the quick start guide for any additional setup instructions.
Experience the Power
With the Tenstorrent Grayskull AI Accelerator up and running, you can now experience the incredible power it brings to your AI and machine learning projects. Enjoy faster training times, improved model accuracy, and seamless integration with popular deep learning frameworks.
Are you ready to unleash the full potential of your AI projects? Then the Tenstorrent Grayskull AI Accelerator is the perfect tool for you.
Get a consumer card with 48gb or more memory out there for less than 1500$ and you'll make hundreds of billions on edge AI computing. Pls free us from the green giant and his little red minion.
I'm hoping dev support is added to onnxruntime via wsl2 or even on windows. Didn't understand why compilation is necessary for Python. Does it compile to c or c++ and then throw exceptions or errors wrt libxyz.c or cpp?
I'm very interested to know what Tenstorrent's plans are, if any, for getting their Linux drivers upstreamed into the mainline kernel. Having upstreamed drivers would really go a long way in giving me confidence these cards are going to have long term software support, independent of the fortunes of the company which created them.
What can i do with this card?
Good commodore tshirt. ❤
Doctorate in FPGA, impressive
I was originally very enthousiast on risc-v.
But what I hear and see, is that is is just not performant and crashes continuously.
I am hopeful for the future, but until it is picked up by a credible company like Qualcom / Intel / AMD / Nvidia / ARM / Samsung / …, I doubt it will get to a mature point.
The logo will be something that will catch the attention of AMD's legal department…
If I would be judge / jury in a trial on the IP, I would most certainly see a conflict with AMD's logo.
OKAY ! WHAT IS AI Accelerator again!??!! CUZ YOU ALL SHOWING HARDWARE BUT IT JUST SOFTWARE!! why keep showing me pci-card when you can literally use usb.2!!
is it funny to sell FREE-chatgpt as a new monster graphic chip!!??
i not gamer to fool me by DLSS & RTX !! YOU TALKING TO I.T VIEWER NOT SOME HOME GAMING USER! SO WHO YOU WANT TO FOOL WITH THIS??! WHO!!
I'm interested. What kind of performance difference between Nvidia graphics cards you get with these accelerators?
I'm assuming it's not as good as a 4090 or something, but it's still probably significantly better than just running on my 16 core CPU.
So like where in that range does this thing sit? Or is it more about the interesting framework that enables more creative development?
Would be nice if you can use it in combination with Matlab, interesting product. Interesting woman very eloquent.
This reminds me of the Physx add-in cards some 15 years ago. Unfortunately for them, single graphics cards very quickly became fast enough to do in-game physics themselves without requiring a separate card for the purpose. NVIDIA just swallowed Physx whole… as it had done with 3dfx before it. Since then, NVIDIA’s dominance has become all-encompassing. I’ve known NVIDIA almost since its inception…. it’s a hard-nosed company that takes no prisoners. My advice for other A.I. companies is to keep out of NVIDIA’s crosshairs.
Not heard Jim Keller mentioned since he bailed out of the Ryzen project in 2015. Considering how bad those early CPUs were I’m guessing AMD didn’t listen to his advice. Pretty sure he wouldn’t think having the cache speed locked to RAM speed would be a good idea.
what card do i need for a local LLM
Benchmarks?
Is Ian flirting? 😂
8gb of lpddr4…….. for $599…….. bruh 💀. it’s an interesting project don’t get me wrong, but I could do better with an off-the-shelf Nvidia gpu.
Sorry to use this reference, but as SJ used to say, "Great Products Ship". You cannot try things out unless they're manufactured and in your hands. 'Announcements' don't run LLMs. 😸
I hope these specialized chips completely take over the inference market and that future chips take over training at scale too.
I would like to see sane prices for GPUs again.
Is this the SDI/3dfx 3d accelerator moment for AI Accelerator's?