I was sent this great summary by the Financial Times about the Areva and its EPR situation. EPR are the latest generation of nuclear power plants. The one designed to secure us against future Fukushima. There are four of them in construction around the world. And those projects by its size are regularly brought up in the news for its delay and cost overruns. This article summarizes some of the reasons which explain the delay by 6 to 9 years and the overbudgets by billions.
The conclusion of the article is from the outgoing Project Manager who stated: “EDF (French Power Producer who merged with Areva) has full confidence that we won’t repeat the mistakes of the Finnish and French EPRs”.
Delay are expected as part of the project lifecycle. Afterall going from the drawing board to the concretisation of a complex idea is extremelly tricky, and requires lots of creativity, intelligence and persistance. We can’t expect to go without mistakes on a new project that has such an ambition: make nuclear power safe.
“Errare humanum est, perseverare diabolicum”
If mistakes and delays are acceptable; redoing the same mistake isn’t. Any project structure need to ensure that the knowledge is captured as much as possible with the goal to learn for our mistakes!
Lili uses artificial intelligence to gather and pushes the right information from any of your projects around the world, so the project team can decide with the right data on hand.
This is an amazing interview with Prof. Yann Le Cun, Director at Facebook AI and Professor at New York university. Unfortunately it is in French: http://www.franceinter.fr/emission-les-savanturiers-yann-lecun-chercheur-en-intelligence-artificielle
My favorite highlights are:
- Intelligence is the ability to predict by observing it.
- In the future, Virtual Assistant will help us in our daily lives to access the right information, to explain us stuff, to communicate with other people, answer any kind of question, etc.
- In the future, robots will be able to perform tasks that annoy us.
- Deep learning will make the world better, reducing human suffering, automating painful tasks, etc.
- Robots will have feeling. Emotions are related to prediction. Fear is related to predicting something scarry. Robots will be able to predict, hence they will have simulated emotion.
I had the chance to meet the very inspiring Prof. Yann Le Cun at his course at College de France where he was teaching a serie of courses about Deep Learning. I highly recommand anyone interested in machine learning AND speaking French to check out those classes. All the course are posted here: http://www.college-de-france.fr/site/yann-lecun/_agenda.htm
Virtual Assistants are for sure a new and rising segment for AI! Here is a short list of the many innovations that applies AI to Project Management: customer service, team ordering, scheduling, financial assistant, etc.
There are actually many more including Facebook M. and Google now.
Ready for Lili, the first virtual Assistant in Project Management?
In 1986, the space shuttle Challenger exploded. Could this “predictible surprise” be avoided? Mike Mullane believes that it was a succession of mistakes that caused NASA’s first in-flight tragedy.
Especially when pressure is high, the team feels under pressure and wrong decision can result of it. Project Management is about quality, not quantity!
At Lili, we believe that a strong Project team is for and foremost a team of individuals who are willing to work together because they can rely on each other. The indirect result of this mutual trust is more efficiency, reactivity, compliance and alignment for the corporate.
The Challenger Launch Decision, Diane Vaughan (1996)
Start-ups live are full of up and down. Today looks like an up up day.
Very often people ask me: “why do you feel that Lili will succeed in reinventing Project Management? Why would it be more successful than an Asana or Jira which have raised significant money and have huge user base?”
My answer is simple: “We are different.
1/ We have a unique vision. A vision where projects are delivered smoothly because all the project teams gain years of experience supported by the AI. Lili is not only a great mathematics problem; it is especially a huge human pain!
2/ We target huge complex waterfall projects vs. Agile and start-ups . I only know PM at billion dollars companies (GE, P&G, Deloitte, Credit Suisse, European Union, SNC Lavalin, AGS Four Winds, …) and their teams seriousely need some AI to simplify their very processful life.
3/ Or did I mention the team? We have a top-tier board of Advisors and collaborators.
So yes, we believe we belong to this class of new start-ups ready to implement AI in the business world. We pick Project management and we won’t stop until we change the PM world.
This thought was inspired by this article : http://venturebeat.com/2016/04/02/deep-learning-will-be-huge-and-heres-who-will-dominate-it/
I believe technologies should almost come as a complement to human beings in order to help them complete their basic needs! Here is an example.
Welcome to the first Cyborg Olympics!
Videos and text available here:
Machine learning allows algorithms to learn through experience, and do things we don’t know how to make programs for.
To Domingos (University of Washington computer scientist Pedro Domingos), machine learning is as big of a breakthrough as personal computers, the internet, or electricity itself.
“There were two stages to the information age,” Domingos says. “One stage is where we had to program computers, and the second stage, which is now beginning, is where computers can program themselves by looking at data.”
Perhaps that’s why Google’s Eric Schmidt says that every big startup over the next five years will have one thing in common: machine learning.
Full article: http://www.techinsider.io/machine-learning-as-important-as-the-internet-2016-3