Sunday, November 13, 2016

Apcera re-purposed itself.


Apcera started as a PaaS platform called Continuum; then HCOS (Hybrid Cloud Operating System); then simply Apcera  platform.

The latest Apcera incarnation from Network World Nov 8  is
 Apcera’s container management platform for cloud-native and legacy applications. At the same time, the company also announced it has expanded integration features to further support Amazon EC2 Container Service (Amazon ECS), Google Compute Engine and Microsoft Azure—strong integrations that should further the company's claim to providing near-seamless movement of workloads across heterogeneous environments.
According Mark Thiele, chief strategy officer for Apcera.
“Apcera has an enterprise-first approach to container management, and customers regularly turn to us to help modernize legacy applications, as well as to run Docker securely and at scale,”


There is a January 2015 - famous now - blog from Bryan Cantrill, Joyent CTO . The title is Predicteria 2015 . If you wonder what Predicteria means, Bryan told me and I wrote it down in this The new Joyent blog.

According to Bryan
  1. 2015 is the year of the container. ... Thanks to Docker, the world is finally figuring out that OS-based virtualization is actually highly disruptive (better performance and lower cost!), and I think that this realization will become mainstream in 2015. I don’t think that Docker will necessarily be the only substrate,
  2.  The impedance mismatch between containers in development and containers in production will be a wellspring of innovation. Currently, containers have a ton of developer enthusiasm — but limited production deployments, in part because of production concerns around security, persistence and network virtualization. But it’s a sure bet that there will be (many) players tackling the problems in interesting ways.
 I asked, how did  he notice the impedance mismatch?
When I speak to a developer event, I ask people the audience: "How many of you have used Docker containers?"  About one third to half of the audience raises the hand. Then I ask:  "How many of you have used Docker containers in production?" and I see just a few hands  still up
I am convinced it was the vision of Bryan that lead Joyent to re-invent itself

Why Docker is a winner versus VMs

This is the title of my LinkedIn blog . I am humbled by the traffic generated from Docker, Quora and LinkedIn

I ended the article like this
If Docker is a contract between devs and devops, then Apcera's HCOS seals it in form of ITOps policies that make it  respected and implemented in an automated fashion
I still believe this today.

Friday, November 04, 2016

How to stop AI bots from creating a Mad Max world

What Cooldimi offers?

We enable intelligent Chat-Robots, in short Bots. We make a bot smarter. To use an analogy, a hunter needs a dog. But this is not any dog, but a special breed and trained as a hunting dog.

Similar to a hunting dog, a cooldimi bot learns faster to make successful it's owner, knows it's  limitation and lets the human take initiative when it has no answer, It will quickly learn new skills to improve his owner satisfaction.

We have demo available  on how we actually do this with a bot, any bot from Facebook, Microsoft, Pandorabot and so on.

What can I do with a bot?

Before answering this question, Facebook’s introduction of a bot-building platform at its F8 developer conference event April 2016, triggered indirectly some colossal profit increase for the company. Facebook had a wildly successful Q3, earning $7.01 billion in revenue. Facebook destroyed analyst estimates, which were $6.92 billion in revenue 
The first thing you can do with a bot you can make money for your company.
This is Cooldimi's bot platform ultimate goal.

Do all bots have intelligence?


Do you mean machine learning intelligence?  No. Most of them are rules based. Like this Rubik's Cube Kuldip Pabla (Cooldimi CTO) built in one day for his son who trains for Rubik speed solving competitions.

So what is Cooldimi?

Cooldimi is bot platform.   It enables Conversational Economy, meaning one can order services and manage infrastructure with leaving the messenger chat.

It focuses on industry specific (narrow) domains, For example a bot calling an Uber car can not be used for email promotions

Cooldimi measures happiness factor using human sentiments It  blends Artificial Intelligence with Human Intelligence.

Cooldimi makes bots that meet business specific goals  and the users are happy. People never buy something they are not happy with.

Cooldimi adds a meaningful conversation in a suitable narrow domain. with clear business goals, directly or  indirectly, and we intelligently monitor the bot to make sure it delivers. Do you want to make money?

That will be nice.

Cooldimi makes the difference between (money-in to  garbage-out) versus (money-in to a-lot-more-money-out)

Can Artificial Intelligence appear as human intelligence?

Not  in the foreseeable feature

According to WILDML blog 
Many companies are hoping to develop bots to have natural conversations indistinguishable from human ones, and many are claiming to be using NLP (Natural Language Processing)  and Deep Learning techniques to make this possible. But with all the hype around AI it’s sometimes difficult to tell fact from fiction.
 Most of the value of deep learning today is in narrow domains where you can get a lot of data. Here’s one example of something it cannot do: have a meaningful conversation. There are demos, and if you cherry-pick the conversation, it looks like it’s having a meaningful conversation, but if you actually try it yourself, it quickly goes off the rails.

What do you mean "it quickly goes of the rails?"

If you’ve actually used any of the personal assistants (PSa) you may be skeptical. Siri still barely understands what you want, and Facebook has put hordes of human workers behind Facebook M to get it to do anything useful. How will these things ever replace all the complex tasks we’re doing apps and browsers? 
So you need human intervention. Machine learning can not sort it out by themselves, Have you heard Microsoft TAY?

I did. It made an uproar. How it happened?

It is a failure that was a success, as we learned so much from it. See Microsoft’s disastrous Tay experiment shows the hidden dangers of AI  
Microsoft’s disastrous chatbot Tay was meant to be a clever experiment in artificial intelligence and machine learning. The bot would speak like millennials, learning from the people it interacted with on Twitter and the messaging apps Kik and GroupMe. But it took less than 24 hours for Tay’s cheery greeting of “Humans are super cool!” to morph into the decidedly less bubbly “Hitler was right.”

How Coodimi avoids a Mad Max invasion?

The domain millennials mean all people aged 18 to 36 . This a huge land, impossible manage to via artificial intelligence, where one starts training a bot with an initial conversation, and improves this conversation as the bot gets used more and more. A bot has no notion of ethics. The users take control of the space creating out of Chaos an unpredictable world. Just like the movie Mad Max, a 1979 Australian post-apocalyptic dystopian action film.

24m of Twitter‘s 284m active users are bots with “no discernible user action involved”,  This was back in January 2015. Today the number can be much larger.

A clear domain narrowing is key for enabling  business bots that deliver results

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AI and ML for Conversational Economy