GDA Fund

This video is the fourth series covering the GDA Crypto Open Data Initiative. We start with a focus on HFT Predators; we give a broader coverage of this subject than we did in the third video. We then discuss High performant blockchains like Solana and talk about Serum. After, we talk about how advances in Algorithms/Sofware and hardware are essential to the future of Defi 2, what the possible next steps are going to be, and how Neuromorphic computing and AI fit into the picture in Decentralised intelligence. In the following videos, we will be discussing HPC in Python and Intels Nueromphic Hardware.

Here we focus on how GDA atomic events can be aggregated and used as data features for our DNN. We mention how Neuromorphic hardware breaks the Von Neuman Barrier and achieves neuromorphic supremacy, especially when looking at Neuromphic Photonic hardware.

Also, we look at plasticity. One of the most appealing features of neural systems is plasticity, i.e. the natural ability to learn and adapt to an unpredictable and changing environment. Therefore, a vital stage towards developing truly bio-realistic photonic neuromorphic hardware is the photonic implementation of plasticity in artificial synapses and neurons.

Achieving Graphine Oxide-based laser patterned photonic memristors with sizes comparable to those of the biological synapses (20–40 nm) It will require fabrication methods able to go beyond the diffraction limit. Technologies such as super-resolution photoinduction inhibited nanofabrication (SPIN)

Real-life use case of how high performance computing can be used in high-frequency trading, using optimisations which target the Intel Architecture. Many other use cases can benefit from the same methodical approach. Talks on GPU’s CUDA and FPGAs Verilog and Photonic Neuromorphic computing, Spiked Neural Networks are in the pipeline.

GDA Fund

GDA Fund

GDA Holdings Ltd is a crypto fund. GDA is developing a new generation of quant workflow environment and sophisticated trading engine for crypto market.