[18/06, 1:08 am] ☸️ Danny 心: https://vt.tiktok.com/ZSQsGf9ur/
@HighLevelWithJonathan:Reskilling into what then? That's the question many are struggling with.
@Babe:New jobs in high demand:-
1. AI creator & R&D researchers (Machine language, NLP, LLM, Computer Vision, neural networks, Deep learning, reinforcement learning, AI cybersecurity, Frontier AI etc)
2. AI developers, AI Agentic apps development (Machine language, python programming)
3. AI Agentic users
4. Forward deployed engineer (gather and formulate user requirements into AI development)
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Existing IT professionals jobs:-
1. Cloud professionals
2. Cybersecurity professionals
3. System & Servers IT professionals
4. Network IT professionals
5. Storage, Database IT professionals.
6. Software engineers.
[18/06, 1:09 am] ☸️ Danny 心:
@Babe:1. All AI professionals need to be bilingual:-
a. Possess the AI technical skills.
b. Learn the trade domain - in which AI is to be deployed.
(Eg. If need to AI bank's functions and operations, AI professionals need to know the bank's trade and which aspects of bank operations to AI - in order to reap productivity.
Working with bank users, bank software developers, COO, CTO, CEO - all the C-suite will be critical for success.
Likewise if to AI manufacturing, healthcare, f&b, logistics supply etc - same approach to AI like AI banks).
2. AI users need to be trained in:-
a. Agentic AI develop by AI developers - to reap specific business functions productivity.
b. Use public AI LLM to reap general job productivity.
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@Babe:To illustrate what we can do and what we will be doing in an AI era:-
1. Government
2. Big Enterprise - DBS
@Babe:1. Eg. Government, big public enterprise use AI models, LLM and transformer engine develop by Big Tech but use internal dataset and accessible only by the internal government staff.
At no time, the data set will be leaked to the public.
2. The AI architecture uses air-gapped network and the AI transformer engine and LLM run on internal servers and GPUs, internal clouds and internal datasets.
Permission are granted to internal staff based on strict access control with local content filtering on internal data access.
3. This is like using Microsoft OS, install in servers developed by US companies but network are designed by government IT staff with air-gap, firewall and protected within an intranet not accessible by public. The AI architecture and infrastructure are reserve for use by internal government staff only.
The AI infrastructure are not controlled by few powerful overseas companies but in the sole domain and control of the government AI staff.
Our government AI staff control, manage and maintain the entire AI models, architecture and infrastructure.
This is similar to our control of Microsoft OS, servers and network bought from US companies.
@Babe:2a. DBS full AI solution are using Microsoft Co-Pilot.
But the entire dataset that DBS access is DBS internal banking datasets.
There are no instance of DBS dataset, customer information held by Microsoft.
DBS has full control of its purchase technologies from Microsoft - such as Microsoft AI Co-Pilot, LLM, Microsoft Azure cloud and Microsoft OS.
Microsoft has no visibility into DBS AI architecture.
2b. DBS AI forward deployed AI engineers will work with DBS top management, DBS users and DBS IT software developers to establish and formulate user requirements for development of AI Agentic apps.
2c. DBS AI developers will then either use python programming, machine language, Co-pilot to develop Agentic AI apps to automate DBS business functions, process that access the internal DBS datasets.
Microsoft has 0 visibility into this Agentic AI apps develop by DBS AI developers.
2d. DBS AI developers are merely riding on the Microsoft AI Co-Pilot LLM.
Just like using Microsoft Azure Cloud and Microsoft OS.
2e. Once the AI Agentic apps are developed, DBS users will be trained to use the AI apps that will improve their productivity by leaps and bounds.
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@Babe:So all the following jobs will be needed and useful.
They are also highly paid:-
@Babe:New jobs in high demand:-
1. AI creator & R&D researchers (Machine language, NLP, LLM, Computer Vision, neural networks, Deep learning, reinforcement learning, AI cybersecurity, Frontier AI etc)
2. AI developers, AI Agentic apps development (Machine language, python programming)
3. AI Agentic users
4. Forward deployed engineer (gather and formulate user requirements into AI development)
----
Existing IT professionals jobs:-
1. Cloud professionals
2. Cybersecurity professionals
3. System & Servers IT professionals
4. Network IT professionals
5. Storage, Database IT professionals.
6. Software engineers.
====
@Babe:So the big question is - for most Singapore workers.
Reskill into what?
Most Singapore workers can be categorized as "AI users".
1. AI users need to be trained in:-
a. Agentic AI develop by AI developers - to reap specific business functions productivity.
b. Use public AI LLM to reap general job productivity.
====
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