CAP
a.i.
POWERING A.I. RESEARCH
CAP a.i. POWERING A.I. RESEARCH IN ASSOSCIATION WITH OUR DELIVERY - - PowerPoint PPT Presentation
CAP a.i. POWERING A.I. RESEARCH IN ASSOSCIATION WITH OUR DELIVERY PARTNERS STRATEGIC PARTNERS & CAP AI WILL BE POWERING A.I. INNOVATION BY SOURCING ACADEMIC SECURING PLACEMENTS CE WILL PROVIDE MENTORSHIP, TALENT FROM TOP IN
POWERING A.I. RESEARCH
DELIVERY PARTNERS
STRATEGIC PARTNERS
IN ASSOSCIATION WITH OUR CAP AI WILL BE POWERING A.I. INNOVATION BY
SOURCING ACADEMIC TALENT FROM TOP LONDON INSTITUTIONS
SECURING PLACEMENTS IN LONDONS MOST INNOVATIVE A.I. START UPS
CE WILL PROVIDE MENTORSHIP, ACCESS TO TECHNICAL EXPERTISE & SUPPORT
WHAT WE NEED FROM THE START UPS / SCALE UPS
CANDIDATE & INCLUDE CANDIDATE ON PAYROLL
THE PROGRAM WILL BE PART FUNDED BY THE ERDF 50% OF EMPLOYEE FUNDING 50% OF EMPLOYEE FUNDING START UPS WHAT YOU GET IN RETURN
TALENT AS PART OF THE PROGRAM
FOR START UPS – How it works
APPLY FOR CAP AI CAP A.I. WORKSHOP
FIND THE CANDIDATE
Form
aid has been received
activity for CAP AI candidate
Knowledge Broker to your company
problem in a workshop session
report and map requirements needed by candidate
right candidate to meet the requirements of the job
candidates that are capable of the job
right one for you
FOR A.I. CANDIDATES – How it works
APPLY FOR CAP AI
Form
experience in the field
relevant for the A.I. task
INTERVIEW
interview depending on requirements
demonstrate skillset and experience in the A.I. task
research can be commercialized and how you suggest both parties benefit from engaging in the program
GET STARTED
get started
facilitating the employment contract
innovation
CAP A.I. STRUCTURE – How do we help along the way?
MENTORSHIP
the candidate
necks
guidance on how to progress
knowledge base for specialist support
BUSINESS SUPPORT
hardware and infrastructure
candidate to Digital Catapult for computational resource
Learning Lab
consulting for A.I.
PROJECT MANAGEMENT
project
hit
delivery of A.I. product / project
businesses to innovate and get commercialized A.I. products
Decisions
How are predictions used to make decisions that provide the proposed value to the end-user?
ML Task
Input, output to predict, type of problem.
Value Proposition
What are we trying to do for the end- user(s)?
Data Sources
Which raw data sources can we use? (internal/external)
Collecting Data
How do we get new data?
Features
Input representations extracted from raw data sources.
Building Models
Which is the right model? How can we ensure our results are correct?
Making Predictions
How do we want to formulate
Offline Evaluation
Methods & metrics to evaluate the system before deployment.
Live Evaluation & Monitoring
Methods & metrics to evaluate the system after deployment, and to quantify value creation.