Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,146 @@
|
|
| 1 |
-
---
|
| 2 |
-
license: mit
|
| 3 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
---
|
| 4 |
+
|
| 5 |
+
This is a new kind of model optimization.
|
| 6 |
+
This model is based on Gemma-2-27b-it.
|
| 7 |
+
|
| 8 |
+
A paper is currently being written on the technique. Special thanks to my wife, for putting up with me coding in the basement for too many evenings and weekends for months!
|
| 9 |
+
|
| 10 |
+
## Quickstart
|
| 11 |
+
|
| 12 |
+
```python
|
| 13 |
+
# pip install accelerate
|
| 14 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
| 15 |
+
|
| 16 |
+
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")
|
| 17 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 18 |
+
"google/gemma-2-9b-it",
|
| 19 |
+
device_map="auto",
|
| 20 |
+
)
|
| 21 |
+
|
| 22 |
+
input_text = "Write me a poem about Machine Learning."
|
| 23 |
+
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
|
| 24 |
+
|
| 25 |
+
outputs = model.generate(**input_ids, max_new_tokens=32)
|
| 26 |
+
print(tokenizer.decode(outputs[0]))
|
| 27 |
+
```
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
___________________________________
|
| 31 |
+
# *ADVERTISING BREAK*
|
| 32 |
+
|
| 33 |
+
I’m on the hunt for new challenges and a chance to dive into some exciting research opportunities. Oh, and did I mention I just snagged a top spot on the Open LLM leaderboard? 🎉
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
## CV - Dr David Noel Ng
|
| 38 |
+
|
| 39 |
+
|
| 40 |
+
#### Profile
|
| 41 |
+
Innovation enthusiast, AI-strategist, and interdisciplinary-tech nerd – that's me! With over a decade of experience in research and project management, my professional journey has been largely shaped by my passion for artificial intelligence and its potential to transform various industries. With a solid background in artificial intelligence and machine learning, coupled with a knack for innovation and problem-solving (and a healthy dose of curiosity), I'm excited to bring my skills to a new team.
|
| 42 |
+
|
| 43 |
+
Originally from Australia, where I earned my degrees in Organic Chemistry and Biochemistry, I moved to Germany in 2004. My academic pursuit continued with a Ph.D. in Chemistry at the Max Planck Institute of Biochemistry. Today, I leverage my robust educational background and diverse industry experience to drive AI innovations in a wide range of applications. Hobbies? Lots: I've also built the world's most powerful espresso machine and am working to bring [GLaDOS to life](https://github.com/dnhkng/GlaDOS).
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
___________________________________
|
| 47 |
+
### PROFESSIONAL EXPERIENCE
|
| 48 |
+
#### SENIOR GLOBAL INNOVATION STRATEGIST - ARTIFICIAL INTELLIGENCE
|
| 49 |
+
#### Munich Re | Munich | 05/2023 - Now
|
| 50 |
+
|
| 51 |
+
As a Senior Global Innovation Strategist at Munich Re, my passion is in steering AI/ML strategies, maximizing project impact, and advancing the use of cutting-edge technology. I built the AI Accelerator, which drives the rapid and structured development of AI use-case Implementations.
|
| 52 |
+
#### AI CONSULTANT - LEAD AI ENGINEER
|
| 53 |
+
#### appliedAI UTUM | Munich | 04/2019 - 04/2023
|
| 54 |
+
|
| 55 |
+
In my tenure at appliedAI, I held a leadership role where I spearheaded the successful development and execution of various AI/ML proof-of-concept (POC) and minimum viable product (MVP) projects. I utilized a hands-on approach to drive ideation, planning, and delivery of these solutions for our clients.
|
| 56 |
+
|
| 57 |
+
- AI-Controlled Imaging: Directed a PoC of an AI-Controlled Electron Microscope using Reinforcement Learning for a premier imaging company.
|
| 58 |
+
- Anomaly Detection: Oversaw development of security systems utilizing anomaly detection, integrating diverse technologies to boost client security at the Munich Security Conference..
|
| 59 |
+
- Project Optimization: Implemented AlphaZero-based Graph Optimization for project management in the Nuclear Energy sector.
|
| 60 |
+
- Food Safety: Delivered a PoC for industrial food safety equipment, significantly improving detection sensitivity.
|
| 61 |
+
- NLP Consulting: Consulted on automated document analysis and risk assessment for the European Central Bank, leveraging NLP technologies.
|
| 62 |
+
- Aerospace Anomaly Detection: Developed a PoC for Aerospace manufacturing, using generative diffusion models to create synthetic data for training anomaly detection models.
|
| 63 |
+
- Retail Automation: Applied Vision and Skeletal Tracking for supermarket automation, modernizing retail operations.
|
| 64 |
+
- Public Speaking and Training: Regularly presented talks and training sessions on topics such as KI-Transfer Plus for the Bayerischen Staatsministeriums für Digitales, and KI in Biotech for the BioEntrepreneurship Summit, spreading AI knowledge and fostering digital transformation in the Health/Pharma sector..
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
#### PROJECT LEAD - INNOVATIVE TECHNOLOGIES
|
| 68 |
+
#### Nanotemper Technologies GmbH | Munich | 5/2016 - 3/2019
|
| 69 |
+
|
| 70 |
+
Project Lead in the Future Technologies Department, Scientist Bioanalytics and all-rounder in bioanalytics/data/optoelectronics. Contributions and successes:
|
| 71 |
+
- Created and applied Deep Learning models for interpreting biophysical data for pharmaceutical stability in antibody development
|
| 72 |
+
- Designed, built, and programmed prototype optoelectronic apparatus for the rapid analysis of biosimilar pharmaceutical molecules
|
| 73 |
+
- Introduced FPGA technology for high-speed data collection and analysis, now used in the key products at Nanotemper
|
| 74 |
+
|
| 75 |
+
#### RESEARCH SCIENTIST
|
| 76 |
+
#### Max Planck Institute Of Neurobiology | Martinsried | 02/2016 - 04/2019
|
| 77 |
+
|
| 78 |
+
Driven by an interest in Biotech, I found a role in research working on biosensors, particularly on optical probes of neural activity (Optogenetics). Contribution and success:
|
| 79 |
+
- Designed, built and utilized a robotic screening platform for the high-throughput engineering of biosensors.
|
| 80 |
+
- Utilised image-processing and machine-learning techniques to collect and analyse biosensor data.
|
| 81 |
+
- Automated the development of large molecules by FACS-based directed protein evolution.
|
| 82 |
+
- Patented new CRISPR/Cas9 technology for high-throughput protein engineering.
|
| 83 |
+
|
| 84 |
+
#### CONSULTANT FOR THE NETFLIX SERIES 'BIOHACKERS'
|
| 85 |
+
#### Netflix | Munich | 01/2019 - 12/2019
|
| 86 |
+
|
| 87 |
+
In this role, I advised on the scientific concepts, storylines and film set for this popular Netflix series. Contribution and success:
|
| 88 |
+
- Helped design and build the Laboratory and ‘Biohacking’ labs
|
| 89 |
+
- Modified the scripts to keep scientific accuracy
|
| 90 |
+
- Location scouting and liaison with the LMU to organise research labs for filming
|
| 91 |
+
|
| 92 |
+
#### Doctoral Candidate
|
| 93 |
+
#### Max Planck Institute for Biochemistry
|
| 94 |
+
|
| 95 |
+
My PhD thesis was all about Optical brain-computer interfaces, and synthesizing molecular sensors for optically imaging brain activity. I devised a new biomolecular targeting technique and developed compounds for high-speed optical analysis of neuron activity.
|
| 96 |
+
- Molecular Sensor Development: Designed, synthesized, and tested molecular sensors to optically image brain activity, advancing neuroimaging capabilities.
|
| 97 |
+
- Biomolecular Targeting Technique: Developed a novel technique for labelling live cells with organic dye, utilizing pro-drug techniques used in pharmaceutical development, enhancing the precision of cell tracking and analysis.
|
| 98 |
+
- Neuronal Activity Analysis: Designed a high-speed optical analysis setup for cultured neurons and developed specialized compounds for this purpose, improving our understanding of neuron activity.
|
| 99 |
+
|
| 100 |
+
## SKILLS
|
| 101 |
+
- Strong interest in customer experience and Machine Learning transformations (e.g. expectation management, stakeholder alignment, team reorganization etc.)
|
| 102 |
+
- Ability to work autonomously in the completion of deliverables
|
| 103 |
+
- Ability to provide technical and analytic direction, guidance and roadmaps for ML projects
|
| 104 |
+
- Excellent communication and presentation skills: able to explain Analytics in non-technical terms to business users (C-level, investors, public presentations etc.)
|
| 105 |
+
- Deep technical expertise and strong problem-solving and data-analysis skills
|
| 106 |
+
|
| 107 |
+
|
| 108 |
+
|
| 109 |
+
## AWARDS
|
| 110 |
+
|
| 111 |
+
#### The United Nations COVID-19 Detect & Protect Challenge
|
| 112 |
+
- The United Nations Development Programme Centre for Technology, Innovation and Sustainable Development · Aug 2020
|
| 113 |
+
|
| 114 |
+
#### AI at the Edge Challenge with NVIDIA - Artificial Intelligence of Things (AIoT)
|
| 115 |
+
- Issued by Nvidia · Mar 2020
|
| 116 |
+
|
| 117 |
+
#### Create Intelligence at the Edge - Artificial Intelligence on FPGA
|
| 118 |
+
- Avnet and Xilinx · Dec 2018
|
| 119 |
+
|
| 120 |
+
#### PATENTS
|
| 121 |
+
- WO2018020050A1 - Targeted in situ protein diversification by site-directed DNA cleavage and repair
|
| 122 |
+
|
| 123 |
+
|
| 124 |
+
## EDUCATION
|
| 125 |
+
|
| 126 |
+
#### PhD in Organic Chemistry
|
| 127 |
+
- Max Planck Institute of Biochemistry
|
| 128 |
+
|
| 129 |
+
#### Honours Degree - Biochemistry
|
| 130 |
+
- Monash University Melbourne
|
| 131 |
+
|
| 132 |
+
#### Bachelor of Science - Double Major -
|
| 133 |
+
- Chemistry / Molecular Biology
|
| 134 |
+
- University of Tasmania
|
| 135 |
+
|
| 136 |
+
#### Nanodegree - Deep Reinforcement Learning
|
| 137 |
+
- Udacity Online
|
| 138 |
+
|
| 139 |
+
#### Nanodegree - Deep Learning
|
| 140 |
+
- Udacity Online
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
___________________________________
|
| 144 |
+
I'm based out of Munich, Germany, but I would be interested in working remotely for a team with more compute than my 2x 4090s 🚀
|
| 145 |
+
|
| 146 |
+
#### Reach out via [LinkedIn](https://www.linkedin.com/in/dnhkng)
|