Introduction for i-Teams
Introduction for i-Teams
Jan 17
文章目錄
- Introduction for i-Teams
- Online platform
- Covid
- Zoom rooms
- Amy Weatherup
- Histroy
- samples
- no 1 reason for start up to fail
- No market need (42%)
- timing is everything
- nvoy [an iphone in 2003]
- What went wrong?
- STNC- the first mobile web browser
- What went right?
- Chance favors only the prepared mind---Louis Pasteur
- ITEAM FORMATION
- What
- How does it help?
- Iteams works like like real startup
- What skills are you bringing to your teams?
- Customers
- **Benefits** not features
- Finding contacts
- Some past iteams projects
- Inventor meeting
- Research interests
- Research projects
- Teaching activity
- Research opportunities
- Department role and responsibilities
- Content
- Signaloid
- 1 what
- 2 why do not
- possible relative modest edge devices
- what does it mean for the automatic distributions
- goal2
Online platform
- moodle
- recording
- accouncements
- zoom
- online meeting rooms
- slack
- team communication
- google drive
- Storage
- all materials needed
- Micro.com
- online interactive whiteboard
- workshop
- next week’s brainstorming
Covid
- symptoms and isolations
- masks
- pizza
- 6:30
Zoom rooms
- lectures
- team meetings
Amy Weatherup
- STNC
- Microsoft
- Quuaalcomm
- Start up business development
- commercial and charitable boards
- university teaching
- created and run iteams
- university of cambridge primary school
- birthlight
Histroy
- MIT
- 2006
- Pre-spin-out stage
- Essex
- UoL
- 200 projects
- 1300 students
- 90 start ups founded
- 2/3 still actively commercialising
samples
- raspberry pi
no 1 reason for start up to fail
- overconfidence
- not creating what customer’s need
- poor team structure
- lack of capital
- no market need ！！！！！
- no market
- not right tea
- get completed
No market need (42%)
- Sanity check
- if someone can not find it
- which people
- which company
- how they will pay for it?
- take a different approach at it
timing is everything
- Time
- note
- not taking the
nvoy [an iphone in 2003]
What went wrong?
-
right product, wrong time
-
no viable route-to-market
-
Did not listen, did not solve current problems
-
Customers are not reasdy to take it
STNC- the first mobile web browser
- brining information to people on the move
What went right?
- Right product, right time
- Route-to-market
- business model
- fast and flexible
- paying customer
Time, timing and money is the most important things in life
- Dr. andy richards
- chiroscience, DanioLabs, Arakis and others
Chance favors only the prepared mind—Louis Pasteur
- https://carey.jhu.edu/one/2010/fall/the-mind-of-the-enterpreneur
ITEAM FORMATION
- new technology from cambridge lab
What
- Analysis and recommend
- best target applications for new technologies
- no commercial application
- valid and useful answers
- no commercial application
- best target applications for new technologies
- use real feedback
- industry experts
- not just an interest exercise
- industry experts
- your maintask real world feedback on your technologies
- Geoffrey Moore in Crossing the Chasm
- What is the one application that best captures the power and value of your technology?
How does it help?
- Work on real inventions while still in the lab
- look for real world uses that solve real customer problems
- is it good match
Iteams works like like real startup
- iteams
- interdisciplinary
- Mentoring
- Contact
- repeated revision of conclusions required
- startup
- complimentary skills
- Feedback
- Contact
- Re[eayed review of progress and direction to ensure success
What skills are you bringing to your teams?
Customers
- paying money to your product
- sustainable business need paying customers
- government grants and investment can help you started, but they are not customers
- get the people willing to pay
- people willing to pay
Benefits not features
- do something new
- do something better
- behaviour change takes a generation
- beware of assumptions
- cheaper
- safer
- cleaner
- quicker
- less manual efforts
- LARGE AND SMALL ONE
- actually they are not the key things
- actually, the industry want to see the best performance of the sensors
- make the associated insights
- problems for our technologies to make the implications
Finding contacts
- Identify companies working in the relevant area
- try different search terms
- wikipedia
- relevant industry market report
- patent searching for relevant technical
- Ways to looking for fields in the domain
- finding out more about them
- company websites
- company annual reports
- Pre releases and technology white papers
- what they are saying what
- identify people in your target companies
- conference speakers and attendees
- new items/ pre releases
- linkedin
- people talking about their companies
- it is better to give a video call
- which is much more engaging
Some past iteams projects
- Cell cultivator
- what is the technology and what has been done with it?
- Cell cultivator 耕耘機 created to help inventor’s own research project
- needed a controllable environment for observing cells over several weeks
- working model cfreated and used in experiments, refined several times
- we need to know the existance of others by systematic literature review
- what is the technology and what has been done with it?
- What is the technology and what has been done with it?
- South american
- toothache plant
- plant
- commercial
- phase ii human clinical trials
- I-teams
- before
- EU legislation ti
- during
- After
- before
- South american
Inventor meeting
-
MarcBax
-
I assist clients to turn ideas, inventions and insights into tangible, valuable and sellable products. In some cases this means taking a product from proof-of-concept through to volume manufacture. But it can also mean working out a rough idea into an investable proposition by creating concepts and product demonstrators. Value is not intrinsic to an idea, but is created by making it practical, by execution.
I focus on ideas where sensors and sensing play an important role - products that detect, monitor, diagnose, measure or image something. In application fields including medical devices, lab equipment, security/defense, and environmental monitoring.
I’m a mechanical engineer and physicist by education, added a marketing degree through evening study and think I’ve become an all-round product- and business-developer by experience.
For employers in the medical device and printing equipment industries I’ve taken products from concepts through to commercial success. Since 2003 I work freelance mostly for start-ups and SMEs.
Apart from working on product design and development through my company Panchromos Limited I collaborate with my brother Laszlo in Bax & Company, an open innovation consultancy with offices in Spain, the UK and the Netherlands. We set up and execute collaborative innovation projects with an EU perspective (e.g. Horizon 2020, Interreg).
I also volunteer as business mentor for i-Teams projects at the University of Cambridge.
-
-
Philip stanley marbell
-
Research interests
NOTE: The publication list above is auto-generated by the University and is outdated and inaccurate. See below or here for an up-to-date list.
Summary of Recent Research: My research exploits information about the physical world to make more efficient computing systems that interact with nature. This requires a combination of theory (applied mathematics) and hardware (circuits and computer architecture). My research involves equal parts of equations, proofs, circuits, and hardware prototypes. I spent some time in the mid-nineties working at Bell-Labs in the group that created C, C++, and Unix. Partly as a result, I enjoy designing domain-specific programming languages and compilers (inevitably, for problems involving efficient computing systems that interact with nature).
Capsule Bio: B.Sc., 1999 (Rutgers); M.Sc., 2001 (Rutgers); Ph.D., 2007 (Carnegie Mellon). In the summers of 1995, 1996, and 1999, I worked as an intern / engineer at Bell Labs (Murray Hill, NJ), first in the Microelectronics Division, and then in the Data Networking Division, on a project spun out by the research group that created the C programming language, the Unix, Inferno, and Plan 9 operating systems, and much more. I spent 2006–2008 at Technische Universiteit Eindhoven in the Netherlands, joined IBM Research in Zürich, Switzerland, as a permanent Research Staff Member from 2008–2012, and then joined Apple in Cupertino from 2012–2014. I moved back to academia in 2014: I was in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) from 2014-2017 and joined the University of Cambridge as a faculty member in 2017. Since 2018, I am also a faculty fellow at the Alan Turing Institute for Data Science and Artificial Intelligence in London.
I lead the Physical Computation Laboratory, a research group with about a dozen members (three postdocs, two directly-supervised PhD students, two PhD project students from the Faculty of Mathematics, and five M.Eng./M.Res./IIB students from the Nano DTC, Graphene CDT, and elsewhere). I teach one third year / IIA project course (RISC-V Processor Design), one fourth-year / IIB course (Embedded Systems), and serve as a cohort leader for the Part IA Integrated Electrical Project. Additionally, I am leading the Embedded Systems Technology-Enabled Learning (TEL) Pilot Program in Cooperation with the Cambridge University Press and edX.
Recent Professional Service
- Program committee, USENIX/ACM European Conference on Computer Systems (EuroSys), 2020.
- Co-Organizer, Dagstuhl International Workshop 20222 on Approximate Systems, Schloss Dagstuhl – Leibniz-Zentrum für Informatik, May 2020.
- Associate Editor, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2019 to present.
- Vice Chair, ACM Special Interest Group on Operating Systems (SIGOPS), 2019 to present.
- Executive Committee, EPSRC Connected Everything NetworkPlus, 2019 to present.
- Steering Committee, EPSRC Centre for Doctoral Training in Sensor Technologies and Applications (Sensor CDT), 2019 to present.
- Steering committee, University of Cambridge Trust and Technology Initiative, 2017 to present.
- Steering committee, USENIX/ACM Hot Topics in Operating Systems (HotOS XVII), 2017, 2019.
- Program committee, USENIX/ACM European Conference on Computer Systems (EuroSys), 2019.
- Program committee, IEEE Symposium on High Performance Computer Architecture (HPCA), 2019.
- Program committee, ACM/IEEE International Symposium on Computer Architecture (ISCA), 2018.
Selected Recent Research Publications
- J. T. Meech and P. Stanley-Marbell, “Efficient Programmable Random Variate Generation Accelerator from Sensor Noise". Accepted for publication / to appear in IEEE Embedded Systems Letters, June 2020.
- N. J. Tye, J. T. Meech, B. A. Bilgin, and P. Stanley-Marbell, “Generating Non-Uniform Random Variates Using Graphene Field-Effect Transistors”. Accepted for publication / to appear in 31st IEEE International Conference on Application-specific Systems, Architectures and Processors, July 2020.
- R. Hopper, D. Popa, V. Tsoutsouras, F. Udrea, and P. Stanley-Marbell, “Miniaturized Thermal Acoustic Gas Sensor based on a CMOS Micro-hotplate and MEMS Microphone”. Proceedings of 4th Functional Integrated NanoSystems (NanoFIS), May 2020.
- P. Stanley-Marbell, A. Alaghi, M. Carbin, E. Darulova, L. Dolecek, A. Gerstlauer, G. Gillani, D. Jevdjic, T. Moreau, M. Cacciotti, A. Daglis, N. Enright Jerger, B. Falsafi, A. Misailovic, A. Sampson, and D. Zufferey, “Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms”. ACM Computing Surveys Vol. 53, No. 3, Article 51., 2020. (Nominated for best paper award.) Available as preprint ArXiv:1809.05859.
- P. Stanley-Marbell and M. Rinard, "Warp: A Hardware Platform for Efficient Multimodal Sensing With Adaptive Approximation. IEEE Micro, vol. 40, no. 1, pp. 57-66, 1 Jan.-Feb. 2020.
- Y. Wang, S. Willis, V. Tsoutsouras, and P. Stanley-Marbell, “Deriving Equations from Sensor Data Using Dimensional Function Synthesis". ACM Transactions on Embedded Computing Systems (best paper award winner), volume 18, issue 5s, (22 pages) October 2019.
- P. Stanley-Marbell and M. Rinard, “Perceived Color Approximation Transforms for Programs that Draw". In IEEE Micro Journal, vol. 38, no. 4, pp. 20-29, July/August 2018.
Selected Recent Patent Grants
- P. Stanley-Marbell and M. Rinard, “Method and Apparatus for Reducing Sensor Power Dissipation". US Patent number 10,539,419, granted 21st January 2020.
- D. Chan, J. Iarocci, G. Kapoor, K.-M.Wan, P. Stanley-Marbell et al. (Apple, Inc.), “Initiating background updates based on user activity”. US Patent number 10,223,156, granted 5th March 2019.
- P. Stanley-Marbell and M. Rinard, “System, method, and apparatus for reducing power dissipation of sensor data on bit-serial communication interfaces". US Patent number 10,135,471 B2, granted 20th November 2018.
- C. de la Cropte de Chanterac, P. Stanley-Marbell, K. Venkatraman, and G. Kapoor (Apple, Inc.). “Smart Advice To Charge Notification”. US Patent 10,083,105, granted 25th September 2018.
- P. Stanley-Marbell, G. Kapoor, and U. Vaishampayan (Apple, Inc.). “Dynamic adjustment of mobile device based on voter feedback”. US Patent 9,813,990, granted November 7, 2017.
Research projects
- Programmable Sensing Composites
Funder: EPSRC (EP/V004654/1). Investigators: P. Stanley-Marbell (PI), A. Barbalace (Co-I), S. Pattinson (Co-I) - OLED Color Power Optimization
Funder: Industrial Sponsor. Investigators: P. Stanley-Marbell (PI). - Graphene-Based Ambient Light Sensing and Signal Processing
Funder: Industrial Sponsor. Investigators: S. Hofmann (PI) and P. Stanley-Marbell (Co-I). - Uncertainty Propagating Processor (UPP) Industrial Demonstrator
Funder: EPSRC Impact Acceleration Account (EP/R511675/1). Investigators: P. Stanley-Marbell (PI). - New Industrial Systems: Optimising Me Manufacturing Systems
Funder: EPSRC EP/R022534/1. Investigators: P. Stanley-Marbell (Co-I). Collaborators: Kent (PI), Bath (Co-I), UWE (Co-I), Imperial College London (Co-I), University College London (Co-I). - Computational and Sensing Vitamins for Construction and Infrastructure
Funder: Industrial Sponsor. Investigators: P. Stanley-Marbell (PI). - Programmable In-Powder Sensors (PIPS) for Real Time Metrology and Data Analysis in Powder Processes
Funder: EPSRC (via MAPP Hub). Investigators: P. Stanley-Marbell (PI). - Continuous In Situ Microstructure and Composition Analysis within 3D-Printed Structures Using In-Chamber Sensors
Funder: EPSRC (via Connected Everything Network Plus). Investigators: P. Stanley-Marbell (PI). Collaborators: Imperial College London (Co-I), Sheffield-Hallam University (Co-I). - Energy, Information-Leakage, and Noise Characterization for Sensor Fingerprinting and Sensor Privacy Guards
Funder: Royal Society Grant RG170136. Investigators: P. Stanley-Marbell (PI). - Graphical Programming with Physical Laws for Engineering Students (Grapples)
Funder: Teaching and Learning Innovation Fund (TLIF) award. Investigators: P. Stanley-Marbell (PI).
Teaching activity
- Module lecturer, CUED 4B25 (Embedded Systems)
- Project lecturer/leader, CUED GB3 (RISC-V Processor Design)
- Course instructor, MIT 6.S194/IAP (Error-Efficient Computing Systems) in IAP 2017.
- Workshop instructor, MIT 6.S977 (Technical Communication Skills for Graduate Students), spring 2016.
- Course instructor, MIT 6.S194/IAP (Error-Efficient Computing Systems) in IAP 2016.
- Advisor, MIT EECS Communication Laboratory (Communication Skills for Engineers), 2015 to 2017.
- MIT Kaufman Teaching Certificate Program, spring 2015.
- From about 2002 to 2005, I took part in the Carnegie Mellon Eberly Center for Teaching Excellence program.
Research opportunities
- Compile-Time Transformations to Induce Optical Illusions in a Vector Drawing Language (available, starting 2020)
- Machine Learning for Sensor Transducer Conversion Routines (available, starting 2020)
- Synthetic Sensors and Digital Sensor Substitution (available, starting 2020)
- Feature Extraction in Multi-Modal Sensor Data by Dimensional Function Synthesis on FPGAs (available, starting 2020)
- Performance and Power Analysis of Sensor Access Schedulers (available, starting 2020)
- Sensor access schedulers (available, starting 2020)
- Virtual Machine / Interpreter for C-like Language on Microcontrollers with Less Than 128k RAM (available, starting in 2020)
Department role and responsibilities
- Designed and introduced new 4th-year undergraduate course, 4B25 Embedded Systems (2017/2018)
- Designed and introduced a new 3rd-year undergraduate project-based course on Computer Architecture with RISC-V, Verilog, and the iCE40 FPGA (2018/2019)
- Cohort leader for IA IEP
-
Content
- five years ago
- program
- Mit-translation program
- technology for embedded system
- accurate system sensors
- interesting things
- patent filing
- lent to spin out-
- examples
- picture description of the problem
- keep the slides brief
Signaloid
-
tesla
-
swirlesland
-
Auto
-
coop
-
computing system
-
how uncertainty they are
-
algorithms
-
large and growing challenge across markets
- computational finance
- customers can we analyze the POE solution
- volatity
- equity
- commity
- models they have today
- predictions
- Price of the stock
- with the signaloid’s technology
- distribution and the uncertainity of the information
- how sure the data things will do
- will you have the single number
- in reality , you have a distribution
- at least, they want you to know the probability of the price distribution
- how sure the data things will do
- healthy
- customer
- can we make repp indicate prediction uncertainty??? what makes the different in normal ai?
- pixals
- estimate the temperature of the skin
- response
- 55 beats
- a distribution for the thing
- can we make repp indicate prediction uncertainty??? what makes the different in normal ai?
- customer
- ai in autonomous systems
- customer
- can we explain uncertainty in decisions of legacy sensor-driven firmware?
- the distribution of the
- customer
- computational finance
-
representation of the uncertainity
-
taking existing software on the computing platforms
-
on the implementations of the algorithms to be implemented today
-
intermediate
-
context
- question
- what do we want to find out
- primary from the renewable energy sectors
- building a sub sea auto veheicles
- behaviour of the auto veicles
- Taking our technology to make their system safer
- automaous system
- automous system interecting with the human
- human robotic
- uav
- driveless car
- full auto
–
- identify specific domain, people, company
- this people is the boss in the domain
- this people is the best in this domain
- they would benefit their
- cloud deployment for analyszing their stage
- they want to see their systems
- find out their person
- who they can
- a lead on the people who will use our product
- if you
- Get
signaloid
- trustworthy data-driven system
- by providing technologies for
- capturing
- storing
- transmitting
- computation
- empirical data
- have uncertainties
- empirical data
- The process
- source of empirical data
- technologies for representing uncertain data
- technologies for storing and i/o uncertain data
- technologies for computing on uncertain data
- legacy host software
- every measurement in nature is related to uncertainty
- Estimate of uncertainity of the things
- specific point to the questions
- seperate from the product
- integrated circuit
- interfaces
- number of standard interfaces
- standard equippments
- integrated circuits for sit behind it
- quantification of the measurement of the uncertainity
- Camera of the phone has the csi
- allow the characteristiction for th
- is it a hardware?
- Scale through cloud api’s growth in services integrating it
- indicator of success: get other cloud platforms / apps building on top of our infracturcture
- Lead market in hardware modules for trustworthy automous
- indicator of success: get autonomous systems integrating our GPU/fpga
- what is your business model?
- product vision
- Go to market
- via cloud deployment
- indicator of succes
- CHIP DESIGN
- PHASE I
- VHDL
- R-T-L; Register-Transistor-Logical design
- PHASE II
- Physical design
- actual circuits
- PHASE I
- Leads in
- route to market
- product line
- prototypes
- partners
- prototypes
- product line
- product line
- product line
- cloud platforms
- edge hardware
- working to make these solutions that happen
- i-teams
- really who have the pains today
- people who understand that they have the problem in the autonomous systems
- you can identify
- have the need to make that
- understand their problem better
- dealing with the problems on the problem they are selling
- eu legistration
- business a lot of businesses in your directions
- gdpr
- Sub industry
- security
-
what are your description on how your product
- Outcome 1
- A large company some
- Outcome 2
- A small company really benefits for your
- real customer who has the real pain point
- Outcome 1
-
I-teams
- a clear distinctions
- not here to sell the technologies
- i-teams
- gather information about the types of the institutions
- get opinions from the technologies
- the roadmap identifided
- get their perceptions in their mind
- where they will deverications from
- intelligence
- produce
- a conversations about the preselling processs
- how do you sell your product?
- which benefits for your products?
- what development chocies do you have to make in order to make it possible to happen
- a clear distinctions
-
we help you get the information on how other people think about it
-
solve your uncertainties problems
-
insulted to
-
do you have an issue about the uncertainity
-
the conservations
-
the business development on their side
- 16 times compared using monte carlo simulations
-
Ecosystems and competition
-
ver
- deployment model sophistication
- cloud+hardware
- hardware only
- cloud compute
- Library/os
- End-user service
- deployment model sophistication
-
hor
- technology solipholicatoion and risk
- classical computation
- confidence intervals
- distribution track
- classiscal interface for NISQ
- Quantum
- technology solipholicatoion and risk
-
Signaled: cloud-navie hardware
-
Over 2000 x faster than the state of art at uncertainity tracking
- computer archiecture
- CMU
- half of the decade in ibm
- apple
- what other people think about the
- 8 publications
- since the first publication
- top picks in the
- key
- Gchq
- the world has the
- uncertainity of the sensor side
- machine learning
a = 0.754354
b = 14.985515
c = -1.106014
-
use my technologies for making perictions
-
values
-
Appreciation
-
floating values
- step things
- representing to make it
- different
- go beyond sensor data
- sensors
- variables
- Uncertainity and distribution data
- uncertainity data
- Uncertainity does not come only from data
- a probability distribution about the
- rador
- flight sensors
- analog
- creating the 3d imagies
- have the measurement uncertainities
- multi paths
- objects in the room
- what you know you should be
- noises
- just because the measurement system, which is ill formed
- signoid sub
- tracking uncertainty
- emperical market data
- push that to the black sore equity for
- making the decision about the trust
- great
- think
- brainstroming
- applications of the technologies
1 what
summary of technologies
-
sentense 1: it is a technology to visualize the uncertainty
-
sentense 2: starting from the cloud computing services now to the edge computing platforms in the future for higher performances.
-
elivator plitch
-
have 20 seconds to hook someone
2 why do not
- dimensions or questions
- potential aspects for that
- it is useful for data analysists for making the interperations
- it is useful for the real data responses
- considerations people will have
- people who need to quanitiy the uncertainity to make the interperations will benefit most
- some applications for high
-
possible relative modest edge devices
-
what does it mean for the automatic distributions
- what are the imagine the systems
- auto
- le
- urban planning
- smart cities
- computer visions
- computer imagines
- archectures
- cost living lab
- tool of understanding of it
- sensors
- how to get people involved in the ICT problems
- How the culture archive them in the databases in a highly
- digital twin for in phd at digital twin
- urban planning
- urban modelling
- peter
- ai in logistics
- franscrio
- digital twin
- living model of
- engine
- Operating at certain minutes per
- cool thins in the
- complex
- harvessing data
- manufacturing
- and data gathering
- making it as broad as possible
- new cities
- new costs
- crm
- one big problem
- ideal to digital twin
- exact copy of this things
- billion of pound
- government product
- trying to make the practical solutions
- digital twins in organizational learning processes
- how digital twins for their knowledge interperinal
- machine learning staff in the staff
- one being the phd
- veronica
- Adium-
- eng
- bachelor
- master
- Electronic
- information
- theory
- machine learning
- second
- natural language processing group
- information extraction
- how well people on
- s
- ug
- csee
- master
- computer vision
- breahing
- healthcare purposes
- ug
- chemical engineering
- Chem engineering
- radio
- Chemical
- sustainable
- neural networks
- y
- neural network
- bay
- confidence
- pattern
- specture
- solution
- hblc
- cambridge
- survival
- academically
- time
- interested to see
- ramioms
- inperformance
- Micro
- read the paper in the
-
Goal
- who are we?
-
Goal1
- understand
- https://signaloid.io/cores
-
goal2
總結
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