- Talks from the healthcare sector
- Cutting edge developments with hardware and AI
- AI and risk mitigation
The December edition will be held in-person. Attendance is open to The Fifth Elephant members only. Purchase a membership to attend in-person conference.
- Data/MLOps engineers who want to learn about state-of-the-art tools and techniques, especially from domains such as automobile, agri-tech and mechanical industries.
- Data scientists who want a deeper understanding of model deployment/governance.
- Architects who are building ML workflows that scale.
- Tech founders who are building products that require AI or ML.
- Product managers, who want to learn about the process of building AI/ML products.
- Directors, VPs and senior tech leadership who are building AI/ML teams.
Sponsorship slots are open for:
- Infrastructure (GPU, CPU and cloud providers) and developer productivity tool makers who want to evangelise their offering to developers and decision-makers.
- Companies seeking tech branding among AI and ML developers.
- Venture Capital (VC) firms and investors who want to scan the landscape of innovations and innovators in AI and who want to source leads for investment in the AI and ML space.
If you are interested in sponsoring, email email@example.com.
"Build vs Buy" - It is not this vs that! Instead, in AI, always Buy then Build
A common dilemma for teams or executives is - to “build internally” or “buy from outside”. In software, both strategies have their own pros n cons. However, when it comes to AI, while the reasoning is much more convoluted, the answer is very simple - always Buy before Build!
In this talk, I will argue that when it comes to AI it is not a question of this or that. Instead Buy before Build in AI should be the default answer for most organizations.
I will further argue that this is a great strategy, even if you have a great AI team internally! Contrary to most AI leaders’ opinions who resist “buying” AI solutions from outside and prefer to “build” since they not only see “external solution” as a threat to their charter but also “buying from outside” as a question mark on their n their AI team’s ability.
I will show why this is a very wrong thinking and how a smart AI leader can leverage the “external AI solution” to eventually “build a great internal AI solution” that is not only technically superior but also economically viable.
The only case where this does not make sense is - if you are an “AI first” organization i.e. organization where the “AI product” in question is the primary offering itself.
- Why when it comes to AI (unlike traditional software/IT) it is not a question of Build vs Buy
- The answer is always buy before build for most organizations
- Understand the reasoning and pros/cons of this
- Understand why the line of reasoning does not apply to “AI first” organizations.