business model, business model canvas, mission model, mission model canvas, customer development, lean launchpad, lean startup, stanford, startup, steve blank, entrepreneurship, I-Corps, Stanford
business model, business model canvas, mission model, mission model canvas, customer development, hacking for defense, H4D, lean launchpad, lean startup, stanford, startup, steve blank, pete newell, bmnt, entrepreneurship, I-Corps, Security, NSIN, SOCOM, sensors, Joe Felter
Team LiOn Batteries - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, LiOn Batteries
GPT-2: Language Models are Unsupervised Multitask LearnersYoung Seok Kim
Review of paper
Language Models are Unsupervised Multitask Learners
(GPT-2)
by Alec Radford et al.
Paper link: https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf
YouTube presentation: https://youtu.be/f5zULULWUwM
(Slides are written in English, but the presentation is done in Korean)
At Netflix, we try to provide the best personalized video recommendations to our members. To do this, we need to adapt our recommendations for each contextual situation, which depends on information such as time or device. In this talk, I will describe how state of the art Contextual Recommendations are used at Netflix. A first example of contextual adaptation is the model that powers the Continue Watching row. It uses a feature-based approach with a carefully constructed training set to learn how to adapt to the context of the member. Next, I will dive into more modern approaches such as Tensor Factorization and LSTMs and share some results from deployments of these methods. I will highlight lessons learned and some common pitfalls of using these powerful methods in industrial scale systems. Finally, I will touch upon system reliability, choice of optimization metrics, hidden costs, risks and benefits of using highly adaptive systems.
business model, business model canvas, mission model, mission model canvas, customer development, hacking for defense, H4D, lean launchpad, lean startup, stanford, startup, steve blank, pete newell, bmnt, entrepreneurship, I-Corps, Security, NSIN, SOCOM, sensors, Joe Felter
Team LiOn Batteries - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, LiOn Batteries
GPT-2: Language Models are Unsupervised Multitask LearnersYoung Seok Kim
Review of paper
Language Models are Unsupervised Multitask Learners
(GPT-2)
by Alec Radford et al.
Paper link: https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf
YouTube presentation: https://youtu.be/f5zULULWUwM
(Slides are written in English, but the presentation is done in Korean)
At Netflix, we try to provide the best personalized video recommendations to our members. To do this, we need to adapt our recommendations for each contextual situation, which depends on information such as time or device. In this talk, I will describe how state of the art Contextual Recommendations are used at Netflix. A first example of contextual adaptation is the model that powers the Continue Watching row. It uses a feature-based approach with a carefully constructed training set to learn how to adapt to the context of the member. Next, I will dive into more modern approaches such as Tensor Factorization and LSTMs and share some results from deployments of these methods. I will highlight lessons learned and some common pitfalls of using these powerful methods in industrial scale systems. Finally, I will touch upon system reliability, choice of optimization metrics, hidden costs, risks and benefits of using highly adaptive systems.
Over the course of the semester I worked on a group project on Netflix. Taking a look into Netflix's history and how they compete against their competitors.
To share the learnings I had from the course –
Supply Chain Analytics Essentials
by
Dr.Yao Zhao,
Professor in Supply Chain Management
Rutgers Business School
(Rutgers the State University of New Jersey)
Offered through Coursera.
Thanks to TamilNadu Skill Development Corporation
Déjà Vu: The Importance of Time and Causality in Recommender SystemsJustin Basilico
Talk at RecSys 2017 in Como, Italy on 2017-08-29.
Abstract:
Time plays a key role in recommendation. Handling it properly is especially critical when using recommender systems in real-world applications, which may not be as clear when doing research with historical data. In this talk, we will discuss some of the important challenges of handling time in recommendation algorithms at Netflix. We will focus on challenges related to how our users, items, and systems all change over time. We will then discuss some strategies for tackling these challenges, which revolves around proper treatment of causality in our systems.
Personalizing "The Netflix Experience" with Deep LearningAnoop Deoras
These are the slides from my talk presented at AI Next Con conference in Seattle in Jan 2019. Here I talk in a bit more detail about the intuition behind collaborative filtering and go a bit deeper into the details of non linear deep learned models.
The dairy sector is among the industries adapting to the digital era, and milk delivery applications are becoming increasingly popular. This comprehensive guide will cover every aspect of developing a milk delivery app, from conceptualization to launch.
Comprehensive Guide On Courier Delivery App Development.pdfJPLoft Solutions
Live tracking is available through the courier app, which lets you track every package and other services. By utilizing on-demand courier services, businesses and customers can avoid delays in product deliveries.
Over the course of the semester I worked on a group project on Netflix. Taking a look into Netflix's history and how they compete against their competitors.
To share the learnings I had from the course –
Supply Chain Analytics Essentials
by
Dr.Yao Zhao,
Professor in Supply Chain Management
Rutgers Business School
(Rutgers the State University of New Jersey)
Offered through Coursera.
Thanks to TamilNadu Skill Development Corporation
Déjà Vu: The Importance of Time and Causality in Recommender SystemsJustin Basilico
Talk at RecSys 2017 in Como, Italy on 2017-08-29.
Abstract:
Time plays a key role in recommendation. Handling it properly is especially critical when using recommender systems in real-world applications, which may not be as clear when doing research with historical data. In this talk, we will discuss some of the important challenges of handling time in recommendation algorithms at Netflix. We will focus on challenges related to how our users, items, and systems all change over time. We will then discuss some strategies for tackling these challenges, which revolves around proper treatment of causality in our systems.
Personalizing "The Netflix Experience" with Deep LearningAnoop Deoras
These are the slides from my talk presented at AI Next Con conference in Seattle in Jan 2019. Here I talk in a bit more detail about the intuition behind collaborative filtering and go a bit deeper into the details of non linear deep learned models.
The dairy sector is among the industries adapting to the digital era, and milk delivery applications are becoming increasingly popular. This comprehensive guide will cover every aspect of developing a milk delivery app, from conceptualization to launch.
Comprehensive Guide On Courier Delivery App Development.pdfJPLoft Solutions
Live tracking is available through the courier app, which lets you track every package and other services. By utilizing on-demand courier services, businesses and customers can avoid delays in product deliveries.
Do you want to explore everything about on-demand app development services? Read our insightful blog today. In this blog, we have discussed about what is on-demand app development and the types of on-demand apps.
Furthermore, we have discussed about how to build on-demand applications and why these apps are popular and high in-demand. Read our blog for more details on this or schedule a call with our tech expert today!
Onyx Beacon: technology and commercial presentation 2015Onyx Beacon
Complete presentation of our solution, including our iBeacons, CMS, SDK and mobile applications. Introducing the most common use cases of our solution: retail proximity marketing, events marketing, asset tracking, smart public transport and hospitality.
Route Optimization Apps unlock productivity and maximize resource utilization. These apps streamline planning and scheduling, optimizing routes to save time, reduce costs, and enhance efficiency for businesses with mobile workforce operations.
The global last-mile delivery software market is forecast to expand at a CAGR of 4.7% and thereby increase from a value of US$70.8 Bn in 2023, to US$97.6 Bn the end of 2030.
Water Delivery App Development With Features and Costamanraza23
Discover a convenient water delivery app with seamless features. Enjoy easy ordering, real-time tracking, and secure payments. Experience hassle-free water delivery at a reasonable cost.
Everything You Need To Know About Food Delivery App Development Cost In Saudi...Techgropse Pvt.Ltd.
Looking for an expert mobile app development company in Saudi Arabia? You have come to the right place.
Our company is a leading provider of mobile app development services in Saudi Arabia, specializing in creating high-quality, user-friendly mobile applications for businesses of all sizes and industries.
Explore how industry-focused Android app solutions can revolutionize your business. These tailored solutions are designed to meet the unique needs of your sector, enhancing efficiency and customer engagement. Ready to elevate your industry's performance? Contact us today and embark on a transformative journey with customized Android apps.
Core principles for successful Ad monetization / Vlad Muntean (Google)DevGAMM Conference
- How do Ad Networks work
- Supply and demand of Ads
- Is a Detailed Mediation Waterfall Necessary
- How to minimize the amount of time necessary for setting up your mediation
- User is King
- The importance of paying attention to users rather than mediation setup
Thomvest Mobile Advertising Overview - February 2016Thomvest Ventures
This is an overview of the mobile adtech ecosystem. Research was conducted by Thomvest Ventures. It covers topics including mobile advertising spend, programmatic advertising, key mobile advertising vendors (i.e DSP, SSP, exchanges & networks), and key trends.
Guide: Turning dormant roamers into revenuesCorine Suscens
This guide outlines a simple strategy to stimulate data roaming usage by enabling data roaming passes to be purchased on the device.
- How an operator increased data roaming revenue by 35% thanks to service passes
- How operators can stimulate spend by using the device as a purchasing channel
- An effective way to provide transparency and cost control, crucial to activate dormant roamers
- The top 5 requirements when considering a data roaming service pass solution
12Return is returns management software for branded and retail companies that streamlines the authorization, transportation, processing and settlement of product returns from consumers and business customers.
How Much Does It Cost To Build A Pickup and Delivery App In 2023?ZimbleCodeAustralia
The popularity of on-demand pickup and delivery apps is steadily rising, transforming how goods are transported. Developing a pickup and delivery app presents a promising prospect for entrepreneurs to venture into this expanding market and leverage its growth potential. Nonetheless, constructing such an app is a multifaceted undertaking influenced by various factors, and the cost involved may fluctuate based on the proficiency of the pickup and delivery app development company, desired features, and required customization.
Industry overview of the mobile user acquisition space going over the ad networks, attribution trackers, and in-app analytics tools.
Also see my Medium post for my information: http://bit.ly/1np5X6s
All recommendations are personal opinion and does not represent Flow State Media.
Pickup and Delivery App Development in 2024: Steps, Cost, Tech StackZimbleCodeAustralia
Creating a pickup and delivery app necessitates an efficient and clean coding strategy, along with optimal resource utilization. Often, business owners encounter pitfalls in the initial development stages.
Therefore, you must hire a reliable on-demand pickup & delivery app development company like ZimbleCode. They prioritize understanding your business requirements and delivering tailored digital solutions that are customizable, robust, scalable, and cost-effective. To learn more, schedule a call with professional experts today!
MartPro provides complete pickup & delivery software for all businesses that provide delivery services. Use this real-time software to improve the customers' experience and optimize employees' efficiency. This platform is designed for all businesses such as courier services, e-commerce, food service, grocery delivery, appointment, and etc.
Similar to Drova Engr245 2021 Lessons Learned (20)
Team Networks - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, networks
Team Quantum - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Quantum
Team Disinformation - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Disinformation
Team Wargames - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Wargames
Team Acquistion - 2022 Technology, Innovation & Great Power Competition Stanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Acquistion
Team Climate Change - 2022 Technology, Innovation & Great Power Competition Stanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, climate
Team Army venture capital - 2021 Technology, Innovation & Great Power Competi...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Army venture capital
Team Army venture capital - 2021 Technology, Innovation & Great Power Competi...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve Blank, Army Venture capital
Team Catena - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, economic coercion,
Team Apollo - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, space force
Team Drone - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, c3i, command and control
Team Short Circuit - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, semiconductors
Team Aurora - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Army venture capital
Team Conflicted Capital Team - 2021 Technology, Innovation & Great Power Comp...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, venture capital
Lecture 8 - Technology, Innovation and Great Power Competition - CyberStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, hacking for defense, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Michael Sulmeyer, cybercom,USCYBERCOM
Lecture 7 - Technology, Innovation and Great Power Competition - SpaceStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, hacking for defense, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, space, space force, general Raymond, space command
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
1. Kamil Ali
Picker
MBA & MS Computer Science, AI
Kimberly Te
Designer
MS Computer Science, AI & HCI
Ariel Leong
Hustler
MS Computer Science, AI
Lydia Chan
Hacker
BS Computer Science, AI
Frank Moss
Mentor
Day 1: Provider for autonomous drone
delivery for food (restaurants and
grocery stores)
105 Interviews
Drova
Now: Fleet management software
for autonomous drone delivery
4. Channels
Businesses - through
warm intros and
contracts; consumers -
through mobile app and
marketing (ex. user
referrals, social media
ads, news)
Customer Segments
Consumers
desiring fast delivery and
reliable/low-touch option
Retail Food/Grocery
Businesses
looking for further reach
and discovery + lower
delivery costs and more
customer satisfaction /
demand
Revenue Stream
Service fee charged per delivery to businesses and customers,
revenue sharing with Drova Partners for profits made through
deliveries completed via their drones
Value Propositions
Problem:
Current delivery services
(human drivers) are slow
and expensive with
limited reach
Need:
Businesses and end
customers are pushing
for inexpensive and
faster delivery with
larger reach
Key Resources
Scalable drone
infrastructure via
franchisees,
public consumer app, route
optimization and
autonomous drone
flight software
Key Activities
Regular ordering of retail
products by consumers
Businesses packaging and
loading items for drone
delivery
Drova Partners locating
drones in demand areas to
service deliveries
Key Partners
Key Partners:
Food/Grocery Retailers
Drova Partners
(Franchisees)
Key Suppliers:
Drone manufacturers
Cost Structure
Fixed cost for starting initial Drone network infrastructure in high-
demand areas (will eventually recoup due to franchisee model),
server costs for developing software models and hosting apps and
services, marketing and sales expenditure
1
Customer Relationships
Established SLAs with
initial business customers
before expanding + two-
way feedback/support
channels with early
customers, recurring deals
and referral rewards for
consumers / strong focus
on consumer support
Original Business Model Canvas
5. Channels
Businesses - through
warm intros and
contracts; consumers -
through mobile app and
marketing (ex. user
referrals, social media
ads, news)
Customer Segments
Consumers
desiring fast delivery and
reliable/low-touch option
Retail Food/Grocery
Businesses
looking for further reach
and discovery + lower
delivery costs and more
customer satisfaction /
demand
Revenue Stream
Service fee charged per delivery to businesses and customers,
revenue sharing with Drova Partners for profits made through
deliveries completed via their drones
Value Propositions
Problem:
Current delivery
services (human
drivers) are slow and
expensive with
limited reach
Need:
Businesses and end
customers are
pushing for faster and
inexpensive delivery
with larger reach
Key Resources
Scalable drone
infrastructure via
franchisees,
public consumer app, route
optimization and
autonomous drone
flight software
Key Activities
Regular ordering of retail
products by consumers
Businesses packaging and
loading items for drone
delivery
Drova Partners locating
drones in demand areas to
service deliveries
Key Partners
Key Partners:
Food/Grocery Retailers
Drova Partners
(Franchisees)
Key Suppliers:
Drone manufacturers
Cost Structure
Fixed cost for starting initial Drone network infrastructure in high-
demand areas (will eventually recoup due to franchisee model),
server costs for developing software models and hosting apps and
services, marketing and sales expenditure
1
Customer Relationships
Established SLAs with
initial business customers
before expanding + two-
way feedback/support
channels with early
customers, recurring deals
and referral rewards for
consumers / strong focus
on consumer support
Original Business Model Canvas
Value Proposition
Problem:
Current delivery services
(human drivers) are slow
and expensive with
limited reach
Need:
Businesses and end
customers are pushing for
faster and inexpensive
delivery with larger reach
6. Channels
Businesses - through
warm intros and
contracts; consumers -
through mobile app and
marketing (ex. user
referrals, social media
ads, news)
Customer Segments
Consumers
desiring fast delivery and
reliable/low-touch option
Retail Food/Grocery
Businesses
looking for further reach
and discovery + lower
delivery costs and more
customer satisfaction /
demand
Revenue Stream
Service fee charged per delivery to businesses and customers,
revenue sharing with Drova Partners for profits made through
deliveries completed via their drones
Value Propositions
Problem:
Current delivery
services (human
drivers) are slow and
expensive with
limited reach
Need:
Businesses and end
customers are
pushing for faster and
inexpensive delivery
with larger reach
Key Resources
Scalable drone
infrastructure via
franchisees,
public consumer app, route
optimization and
autonomous drone
flight software
Key Activities
Regular ordering of retail
products by consumers
Businesses packaging and
loading items for drone
delivery
Drova Partners locating
drones in demand areas to
service deliveries
Key Partners
Key Partners:
Food/Grocery Retailers
Drova Partners
(Franchisees)
Key Suppliers:
Drone manufacturers
Cost Structure
Fixed cost for starting initial Drone network infrastructure in high-
demand areas (will eventually recoup due to franchisee model),
server costs for developing software models and hosting apps and
services, marketing and sales expenditure
1
Customer Relationships
Established SLAs with
initial business customers
before expanding + two-
way feedback/support
channels with early
customers, recurring deals
and referral rewards for
consumers / strong focus
on consumer support
Original Business Model Canvas
Value Proposition
Problem:
Current delivery services
(human drivers) are slow
and expensive with
limited reach
Need:
Businesses and end
customers are pushing for
faster and inexpensive
delivery with larger reach
8. Week 1: Providing food delivery
through an autonomous drone service
We thought...
Restaurants and food services would be our customers, because
they need faster, cheaper, and longer-distance delivery.
1
Customers: Owners of restaurants and food/grocery retailers
9. Week 1: Providing food delivery
through an autonomous drone service
We thought...
Restaurants and food services would be our customers, because
they need faster, cheaper, and longer-distance delivery.
1
So we talked to...
11 owners and managers at restaurants in
North Carolina, where regulations allow for drone operations
Customers: Owners of restaurants and food/grocery retailers
10. Learnings:
- Restaurants are not happy with current
delivery services:
“Doordash takes away our control over the
service we provide to our customers. The fees
are too high and the drivers are not too nice
with customers or the restaurants.”
— Mexican Cuisine Worker
1
11. Learnings:
- Restaurants are not happy with current
delivery services:
“Doordash takes away our control over the
service we provide to our customers. The fees
are too high and the drivers are not too nice
with customers or the restaurants.”
— Mexican Cuisine Worker
1
- Restaurants are hesitant about adopting
new technology:
“We wouldn't use DoorDash… we would have
to carry a tablet around.” — Falafel
Restaurant Manager
“People might shoot down drones.”
— Chicken Restaurant Owner
12. Learnings:
- Restaurants are not happy with current
delivery services:
“Doordash takes away our control over the
service we provide to our customers. The fees
are too high and the drivers are not too nice
with customers or the restaurants.”
— Mexican Cuisine Worker
1
- Restaurants are hesitant about adopting
new technology:
“We wouldn't use DoorDash… we would have
to carry a tablet around.” — Falafel
Restaurant Manager
“People might shoot down drones.”
— Chicken Restaurant Owner
Restaurants are
NOT
early adopters
14. Changes:
Focusing more on software
2
Switch customers from
restaurants to food
delivery platforms
Switch key activity from
operating a drone fleet to
providing software to
enable drone delivery
2
16. Week 4: Diving into Regulatory Problem for
Last-mile Drone Delivery
We thought...
The main challenge in adopting last-mile drone delivery for
food is regulatory compliance based on recurring
complaints by customers.
“If regulatory is not on board, you can never do drone deliveries.”
—Zipline Engineer
4
Customers: Technical and Strategy Leads at Intermediary delivery platforms
17. Week 4: Diving into Regulatory Problem for
Last-mile Drone Delivery
We thought...
The main challenge in adopting last-mile drone delivery for
food is regulatory compliance based on recurring
complaints by customers.
“If regulatory is not on board, you can never do drone deliveries.”
—Zipline Engineer
4
So we talked to...
- Drone delivery services executive leaders and flight engineers
(Deuce Drone, Zipline)
- Autonomous driving engineer (Lyft)
- VCs with prior drone investments (Floodgate)
- Executives at Food Delivery Platform (Doordash, Menufy,
Customers: Technical and Strategy Leads at Intermediary delivery platforms
18. Learnings:
- Food delivery platforms are not early
adopters
“We find drone deliveries to be interesting and agree that it
will be the future of delivery, but we want to see traction
through a few successful pilots before partnering together”
- Director at DoorDash
5
19. Learnings:
- Food delivery platforms are not early
adopters
“We find drone deliveries to be interesting and agree that it
will be the future of delivery, but we want to see traction
through a few successful pilots before partnering together”
- Director at DoorDash
5
- Several key components beyond
regulatory are needed to bring value
to drone delivery
“Regulation is key, and it’s interrelated with product
and engineering.”
- Co-founder of Large Drone Delivery Company
20. Learnings:
Move beyond
regulatory and
expand beyond
food delivery
- Food delivery platforms are not early
adopters
“We find drone deliveries to be interesting and agree that it
will be the future of delivery, but we want to see traction
through a few successful pilots before partnering together”
- Director at DoorDash
5
- Several key components beyond
regulatory are needed to bring value
to drone delivery
“Regulation is key, and it’s interrelated with product
and engineering.”
- Co-founder of Large Drone Delivery Company
21. Drova Service -- Key Modules
Networking Software
(Keeps track of drones and dispatches orders to drones to maximize fleet utilization
and speed of delivery)
Fleet Management Platform
(Commercial drones interoperable with Drova software, drones have compartments
for multiple orders to be serviced in one route, maintained by fleet operators)
Autonomous Flight Software
(Software that enables autonomous BVLOS flight such as detect and avoid
algorithms for moving actors, path planning around flight restrictions, etc)
C2 Communication Software
(Software connecting with command and control systems for safety and control
information relay to manage compliance requirements during all stages of delivery)
Calibrated Landing Software
(Software enabling accurate ground mapping and control for safe, calibrated landing
of drones for consumer pickup in local environments)
Drova:
External
APIs
&
Platform
(APIs
for
order
requests,
tracking
deliveries,
and
item
retrieval
via
drone
compartment)
MVP 2.5: Drone Delivery Integration Software
5
22. Cost Structure
• Fixed cost for starting initial drone network infrastructure in high-
demand areas, revenue sharing for fleet operators long-term
• Server costs for developing software models, hosting apps and
services
• Marketing and sales expenditure
Channels
Businesses - warm intros
and contracts
Customer Segments
Intermediary delivery
platforms (e.g. UberEats)
Revenue Stream
• Subscription fee for businesses
• Revenue sharing with public network fleet operators
Value Propositions
Problem:
Current human delivery
services (human drivers)
are slow and expensive
and have limited reach
Need:
Businesses are pushing
for inexpensive delivery
and larger reach
Customers are pushing
for inexpensive and fast
delivery
Key Resources
• Scalable drone
infrastructure
• Route optimization
• Autonomous drone flight
software
Key Activities
APIs enabling businesses to
incorporate drone delivery
in their workflow
Fleet management software,
regulatory compliance, and
flight for drone deliveries
Customer Relationships
• Established SLAs with
initial business customers
• Strong focus on customer
support
Key Partners
Food/Grocery
Delivery Platforms
FAA (BEYOND
Program)
Drone manufacturers
Fleet operators
5
23. Value Propositions
Problem
Current human delivery
services (human drivers)
are slow, expensive, and
have limited reach
Need
Food businesses are
pushing for inexpensive
delivery and larger reach
Food retailers have
friction with current
human deliverers and
want higher customer
satisfaction
Key Partners
Food/Grocery
Delivery Platforms
FAA (BEYOND
Program)
Drone manufacturers
Fleet operators
Customer Segments
Intermediary food/
grocery delivery
platforms (e.g.
UberEats)
• Technical Leaders
• Strategy Leaders
• SWEs
• Customers: Food
retailers, food buyers
Revenue Stream
• Upfront sales for software
• Subscription fee for businesses
• Revenue sharing with public network fleet operators
Key Resources
• Regulatory compliance: FAA-
approval on for-profit BVLOS
operations
• Physical: Charging stations,
payload containers
• Hardware: Drone fleets, drone
and platform sensors, data servers
• Software: Route optimization,
flight management, landing control,
communications, drone network
management
Key Activities
• Software development kit
(SDK) with APIs enabling food
delivery platforms to add
drone delivery into their end-
to-end delivery workflow
• Platform for fleet operators
to view/manage drone
deliveries
Channels
Direct sales
(software
solutions )
Cost Structure
• Fixed cost for starting initial drone network infrastructure in high-
demand areas, revenue sharing for fleet operators long-term
• Server costs for developing software models, hosting apps and
services
• Marketing and sales expenditure
Customer Relationships
• Established SLAs with
initial business customers
• Strong focus on customer
support
5
Key Partners
Food/Grocery
Delivery Platforms
FAA (BEYOND
Program)
Drone manufacturers
Fleet operators
Key Activities
• Software development kit
(SDK) with APIs enabling food
delivery platforms to add
drone delivery into their end-
to-end delivery workflow
• Platform for fleet operators
to view/manage drone
deliveries
Cost Structure
• Fixed cost for starting initial drone network infrastructure in high-
demand areas, revenue sharing for fleet operators long-term
• Server costs for developing software models, hosting apps and
services
• Marketing and sales expenditure
Customer Relationships
• Established SLAs with
initial business customers
• Strong focus on customer
support
Customer Segments
Intermediary
delivery platforms
• Technical Leaders
• Strategy Leaders
• SWEs
25. Week 6: Focusing further into
Drone Fleet Management Platform
Customers: Companies operating drone delivery
We thought...
Tackling regulatory across modules is too expansive as an MVP.
It is most feasible to focus on one module—fleet management,
supported by ongoing pilot tests with different drone types and
large fleet expectations.
6
26. Week 6: Focusing further into
Drone Fleet Management Platform
Customers: Companies operating drone delivery
We thought...
Tackling regulatory across modules is too expansive as an MVP.
It is most feasible to focus on one module—fleet management,
supported by ongoing pilot tests with different drone types and
large fleet expectations.
Getting out of the building
- Specify fleet management features
- 10 customer interviews with delivery companies using drones
and drone providers (UPS, Zipline)
6
27. Drova Service -- Key Modules
Networking Software
(Keeps track of drones and dispatches orders to drones to maximize fleet utilization
and speed of delivery)
Fleet Management Platform
(Commercial drones interoperable with Drova software, drones have compartments
for multiple orders to be serviced in one route, maintained by fleet operators)
Autonomous Flight Software
(Software that enables autonomous BVLOS flight such as detect and avoid algorithms
for moving actors, path planning around flight restrictions, etc)
C2 Communication Software
(Software connecting with command and control systems for safety and control
information relay to manage compliance requirements during all stages of delivery)
Calibrated Landing Software
(Software enabling accurate ground mapping and control for safe, calibrated landing
of drones for consumer pickup in local environments)
Drova:
External
APIs
&
Platform
(APIs
for
order
requests,
tracking
deliveries,
and
item
retrieval
via
drone
compartment)
6
MVP 2.5: Drone Delivery Integration Software
28. Drova Service -- Key Modules
Networking Software
(Keeps track of drones and dispatches orders to drones to maximize fleet utilization
and speed of delivery)
Fleet Management Platform
(Commercial drones interoperable with Drova software, drones have compartments
for multiple orders to be serviced in one route, maintained by fleet operators)
Autonomous Flight Software
(Software that enables autonomous BVLOS flight such as detect and avoid algorithms
for moving actors, path planning around flight restrictions, etc)
C2 Communication Software
(Software connecting with command and control systems for safety and control
information relay to manage compliance requirements during all stages of delivery)
Calibrated Landing Software
(Software enabling accurate ground mapping and control for safe, calibrated landing
of drones for consumer pickup in local environments)
Drova:
External
APIs
&
Platform
(APIs
for
order
requests,
tracking
deliveries,
and
item
retrieval
via
drone
compartment)
MVP 2.5: Drone Delivery Integration Software
6
29. Goal
Platform that connects, controls, and oversees logistics for different delivery drones.
MVP 3.0: Drone Fleet Management Platform
Users
Drone pilots and delivery workers
Pilot and Drone
Onboarding
Tracking,
Communication,
& Networking
Flight Mission
Control &
Logistics
Drone Fleet
Control &
Operations
Legal, Safety, &
Security
Features
6
30. Learnings:
Too early for
scaling with drone
fleets...
- Positive customer feedback, but the
customers are still in discovery mode, not
scaling with fleets
- “Our endgame is to have a true fleet of
different drone types, where we absolutely
would need fleet management...but we
don’t have a fleet right now.”
- Supervisor of UPS Drone Delivery
Program
6
31. Learnings:
Too early for
scaling with drone
fleets...
- Positive customer feedback, but the
customers are still in discovery mode, not
scaling with fleets
- “Our endgame is to have a true fleet of
different drone types, where we absolutely
would need fleet management...but we
don’t have a fleet right now.”
- Supervisor of UPS Drone Delivery
Program
- Single-use drone modules for logistics and
controls could fulfill customer discovery
needs
6
33. Goal
Platform that connects, controls, and oversees logistics for different delivery drones.
MVP 3.0: Drone Fleet Management Platform
Users
Drone pilots and delivery workers
Pilot and Drone
Onboarding
Tracking,
Communication,
& Networking
Flight Mission
Control &
Logistics
Drone Fleet
Control &
Operations
Legal, Safety, &
Security
Features
6
6
35. Week 8: Honing on Drone Flight Checklists
& Compliance Documentation
Customers: Companies operating drone delivery
We thought...
Our automated pre-flight checklist is the priority submodule feature,
because it necessary and a tedious challenge for all drone flights
(single-use and fleetwide).
8
36. Week 8: Honing on Drone Flight Checklists
& Compliance Documentation
Customers: Companies operating drone delivery
We thought...
Our automated pre-flight checklist is the priority submodule feature,
because it necessary and a tedious challenge for all drone flights
(single-use and fleetwide).
8
So we decided to...
- Build interactive pre-flight prototype
- Test for customer feedback with drone delivery companies,
drone pilots and experts, drone providers, and non-delivery
drone users (inspection, public safety)
37. MVP 4.0: Pre-Flight Checklist
Features:
1. Fleet overview
dashboard
2. Connected with drone
data streams for tracking
3. Automated pre-flight
checklist
4. Detailed breakdown of
action items and safety
level for current flight
8
38. Learnings:
Not quite
product-market
fit
8
- Recurring evangelist interest in solution, but
MVP does not meet their needs yet.
- Many challenges include high variety of
customer needs, tension between drone and
aviation aircraft standards for safety, and
autonomous flight approvals
- “The existing automated checklists by current
services are very poor. We use our own custom
ones, but this varies from smaller businesses to
larger ones. ”
- University Professor in Unmanned Systems,
and Drone Business Owner
39. Learnings:
Not quite
product-market
fit
8
- Recurring evangelist interest in solution, but
MVP does not meet their needs yet.
- Many challenges include high variety of
customer needs, tension between drone and
aviation aircraft standards for safety, and
autonomous flight approvals
- “The existing automated checklists by current
services are very poor. We use our own custom
ones, but this varies from smaller businesses to
larger ones. ”
- University Professor in Unmanned Systems,
and Drone Business Owner
- Could target customization needs in
documentation for launching drone services
(like Clerky)
41. Changes:
Improving our MVP
Revise MVP with
customizable
documentation manager
for launching drone
services
Test with customers
across SMBs and large-
scale delivery
companies
8
43. Customer Segments
• Order fulfillment/ last-
mile delivery logistics
(e.g. UPS-early adopters,
DoorDash-later adopters)
- Technical Leaders
- Strategy Leaders
- SWEs
- Drone
operators/pilots
- End-customers:
package recipients
Key Activities
• Product development
- Platform enabling last-mile
delivery companies to employ a
fleet of drones for delivery
services
-Standardizing registration,
unifying ops workflows and
compliance across drone types
-Dashboard with unified controls
across different drones
-Real-time analytics
• Customer development
• Partnership development
Key Resources
• Regulatory compliance:
Documentation sets for FAA-
approval on for-profit BVLOS
operations
• Hardware: Tracking hardware,
data servers
• Software: Waiver & document
tracking, route optimization, flight
management, communications,
drone network management
Revenue Stream
• Subscription pricing model based on size of drone fleet, # of
different drone types, # of operator users, # of drone programs/use
cases, and customization of offerings/modules
Cost Structure
• Server costs for developing unified programs, software modules,
hosting apps and services
• Product development
• Marketing and sales expenditure
Value Propositions
Problem
• Delivery: Current human
delivery services (human
drivers) are slow, expensive,
and have limited reach
• Other: Performing tasks
which require both broad and
up-close views of large objects
Need
• Delivery: Cheaper costs,
larger geographic reach, tighter
delivery pipeline, reduced risk
of human delivery manipulation
• Other: Drones provide
improved safety, visibility and
flexibility to navigate situations
Product
Drone fleet management
enabling operations &
coordination across different
drone types
Customer
Relationships
• Get: Free trials with
companies seeking fleet
management services
• Keep: Customer support
and customizability
• Grow: Upsell additional
modules to service growing
drone fleet
Channels
• B2B direct sales
(providing software
directly to customers
currently with or without
drone fleets)
Key Partners
• FAA (BEYOND
Program)
• Local government
transportation
departments
• Drone
manufacturers/OEMs
• Pilots/fleet operators
• Order fulfillment/
delivery platforms
- Food/Grocery
Delivery
Platforms
- Food/Grocery
Retailers
Final Business Model Canvas
44. Final MVP
Features:
1. Fleet overview
dashboard
2. Connected with drone
data streams for tracking
3. Automated pre-flight
checklist
4. Detailed breakdown of
action items and safety
level for current flight
5. Documentation
Manager
9
46. Market Size
Total Addressable Market: $6.7B
The market size for drone delivery is estimated to reach $6.7B
Serviceable Available Market: $4.4B
65% of the TAM is projected to be direct to consumer delivery
Target Market: $440M
10% of the SAM is obtainable given heavy need for ongoing regulatory compliance and approval help
Y1-Y3 Revenue: $720K → $4.3M → $18.4M
Estimating active drone subscriptions (20, 120, 512) * 3k per drone
monthly subscription fee * 12 months
Source: https://www.globenewswire.com/en/news-release/2021/05/17/2230618/0/en/At-53-CAGR-Growth-Global-Drone-Package-Delivery-Market-Size-Share-Will-
Reach-to-USD-6773-Million-by-2026-Facts-Factors.html
47. Future Plans
Market Not Ready + Lack of Product-Market Fit
Most companies we targeted were still in the discovery phase and
not in the growth phase.
Our product offering aims to automate processes such as regulatory
compliance and fleet management, but:
- Drone delivery companies are operating at most 5 drones
- Regulatory processes are not defined enough for automation
- Market susceptible to much change
48. Overall Learnings
● More companies are starting to look into drone delivery.
● Although drone delivery companies don’t need our solution today,
they see the need for our service in the future as the regulatory
space and multiple drone operations grows.