“Please give me the bird’s eye view.”
“Please give me the bird’s eye view.”
“…companies like Google and Facebook pay top dollar for some really smart people. Only a few hundred souls on Earth have the talent and the training needed to really push the state-of-the-art [AI] forward, and paying for these top minds is a lot like paying for an NFL quarterback. That’s a bottleneck in the continued progress of artificial intelligence. And it’s not the only one. Even the top researchers can’t build these services without trial and error on an enormous scale. To build a deep neural network that cracks the next big AI problem, researchers must first try countless options that don’t work, running each one across dozens and potentially hundreds of machines.”
Is there value in providing users the ability to apply “Time Lock Encryption” to files in cloud storage? Files are securely uploaded by their Owner. After upload no one, including the Owner, may decrypt and access / open the file(s). Only after the date and time provided for the time lock passes, files will be decrypted, and optionally an action may be taken, e.g. Email a link to the decrypted files to a DL, or a specific person.
Additionally, files might only be decrypted ‘just in time’ and only for the specific recipients who had received the link. More complex actions may be attached to the time lock release such as script execution using a simple set of rules as defined by the file Owner.
The encryption should be the highest available as defined by the regional law in which the files reside. Note: issue with cloud storage and applicable regional laws, I.e. In the cloud.
Already exists as a 3rd party plugin to an existing cloud solution?Please send me a link to the cloud integration product / plug in.
Artificial Intelligent (AI) “Assistants”, or “Bots” are taken to the ‘next level’ when the assistant becomes a proactive entity based on the input from human intelligent experts that grows with machine learning.
Even the implication of an ‘Assistant’ v. ‘Life Partner’ implies a greater degree of dynamic, and proactive interaction. The cross over to becoming ‘Life Partner’ is when we go ‘above and beyond’ to help our partners succeed, or even survive the day to day.
Once we experience our current [digital, mobile] ‘assistants’ positively influencing our lives in a more intelligent, proactive manner, an emotional bond ‘grows’, and the investment in this technology will also expand.
Practical Applications Range:
IBM has a cognitive cloud of AI solutions leveraging IBM’s Watson. Most/All of the 18 web applications they have hosted (with source) are driven by human interactive triggers, as with the “Natural Language Classifier”, which helps build a question-and-answer repository.
There are four bits that need to occur to accelerate adoption of the ‘AI Life Partner’:
Our AI ‘Life Partners’ may grow in knowledge, and mature the relationship between man and machine. Incorporating derived rules leveraging machine learning, without input of a human expert, will come with risk and reward.
FinTech refers to new solutions which demonstrate an incremental or radical / disruptive innovation development of applications, processes, products or business models in the financial services industry. These solutions can be differentiated in at least five areas.
- First, the banking or insurance sector are distinguished as potential business sectors. Solutions for the insurance industry are often more specifically named “InsurTech”.
- Second, the solutions differ with regard to their supported business processes such as financial information, payments, investments, financing, advisory and cross-process support. An example is mobile payment solutions.
- Third, the targeted customer segment distinguishes between retail, private and corporate banking as well as life and non-life insurance. An example are telematics-based insurances that calculate the fees based on customer behaviour in the area of non-life insurances.
- Fourth, the interaction form can either be business-to-business (B2B), business-to-consumer (B2C) or consumer-to-consumer (C2C). An example are social trading solutions for C2C.
- Fifth, the solutions vary with regard to their market position. Some for example provide complementary services such as personal finance management systems, others focus on competitive solutions such as e.g. peer-to-peer lending.
Global investment in financial technology increased more than twelvefold from $930 million in 2008 to more than $12 billion in 2014
Is it all about being the most convenient, payment processing partner, with an affinity to the payment processing brand? It’s a good place to start; the Amazon Payments partner program.
Throughout my career, I’ve worked with several financial services teams to engineer, test, and deploy solutions. Here is a brief list of the FinTech solutions I helped construct, test, and deploy:
A “Transaction Management Solution” targets a mixture of FinTech services, primarily “Payments” Processing.
Target State Capabilities of a Transaction Management Solution:
Is Intuit an acquisition target because of Quicken’s capabilities to provide users consistent reporting of transactions across all sources? I just found this note in Wiki while writing this post:
For quite some time companies have attempted to tread in this space with mixed results, either through acquisition or build out of their existing platforms. There seems to be significant opportunities within the services, software and infrastructure areas. It will be interesting to see how it all plays out.
Inhibitors to enclosing a transaction within an end to end Transaction Management Solutions (TMS):
Those inhibitors haven’t stopped these firms:
Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.
In this fight — no doubt in its early stages — the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.
For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show “Jeopardy!” Today, Watson is the centerpiece of IBM’s A.I. efforts.
Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.
The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…
In the old days, you never knew which CDs the record store would have in stock. That limitation of physical media was supposed to be solved by digital. Back in the 1990s, technology evangelists and music fans alike began to talk about a “celestial jukebox” — a utopian ideal in which every song ever recorded would be available at a click. In reality, even a celestial jukebox has gaps. Or more precisely, numerous jukeboxes have come along – iTunes, Pandora, Spotify, SoundCloud, YouTube – and each service has had gaps in its repertoire. And those gaps have been growing bigger and more complicated as artists have wielded more power in withholding their music from one outlet or another.
Published music libraries are numerous, and have scattered artist coverage for one reason or another. Music repositories may overlap, or lack completeness of coverage.
As expressed in “As a Data Deluge Grows, Companies Rethink Storage“, creating a system similar to the Internet Domain Name System for “Information Asset Libraries” would help in numerous ways. Front end UIs may query these “Information Asset (object) libraries” to understand the availability of content across the Internet.
Another opportunity would be to leverage the existing DNS platform for managing these “Information Asset Repositories”
In a relatively cost restrained implementation, a DNS type effort can be taken up by the music industry. From artists to distribution channels, existing music repositories can be leveraged, and within months, a music aficionado may go to any participating platform, and search for an artist, title, album, or any other indexed meta data, and results across ‘Information Asset Repositories’ would be displayed to the user with a jump link to the registered information asset in the library.
Small independent artists need just populate a spreadsheet with rows that contain a row for each asset, and all the ‘advertised’ meta data. Their Information Asset library may be a single flat file, i.e. XML, that conforms to a basic record/row structure. The independent artist places this file on their web site, e.g. in their root folder, and informs their ISP of the address record type, and it’s location. A new DNS record specification may need to be created, e.g. MX record.
At Pure Storage, a device introduced on Monday holds five times as much data as a conventional unit.
- IBM estimates that by 2020 we will have 44 zettabytes — the thousandfold number next up from exabytes — generated by all those devices. It is so much information that Big Blue is staking its future on so-called machine learning and artificial intelligence, two kinds of pattern-finding software built to cope with all that information.
- Pure Storage chief executive, Scott Dietzen, “No one can look at all their data anymore; they need algorithms just to decide what to look at,”
Pure Storage is looking to “compress” the amount of data that can be stored in a Storage Array using Flash Memory, “Flashblade”. They are also tuning the capabilities of the solution for higher I/O throughput, and optimized, addressable storage.
Several companies with large and growing storage footprints have already begin to customize their storage solutions to accommodate the void in this space.
Building more storage arrays is a temporary measure while the masses of people, or fleets of cars turn on their IoT enabled devices.
Data is flooding the Internet, and innumerable, duplicate ‘objects’ of information, requiring redundant storage, are prevalent conditions. A registry, or public ‘records’ may be maintained. Based on security measures, and the public’s appetite determine what “information objects” may be centrally located. As intermediaries, registrars may build open source repositories, as an example, using Google Drive, or Microsoft Azure based on the data types of ‘Information Objects”
Note: there are already ‘open’ platforms being developed and used for several industries including medical; with limed access. However, the changes I’m proposing imposes a ‘registrar’ process whereby portals of information are registered, and are interwoven, linking to one another.
It’s an issue of excess weight upon the “Internet”, and not just the ‘weight’ of unnecessary storage, the throughput within a weaved set of networks as well.
Think of it in terms of opportunity cost. First quantify what an ‘information object’, or ‘block of data’ equates to in cost. It seems there must already be a measurement in existence, a medium amount to charge / cost per “information object”. Finally, for each information object type, e.g. song, movie, news story, technical specifications, etc. identify how many times this exact object is perpetuated in the Internet.
Steps on reducing data waste:
Another opportunity to organize “Information Asset Objects” would be to leverage the existing DNS platform for managing “Information Asset Repositories”. This additional Internet DNS structure would enable queries across information asset repositories. Please see “So Much Streaming Music, Just Not in One Place” for more details.
Although I fail to see the excitement and mass appeal of aerial drone use, the hobby has taken off on the tail end of military UAV. Just like the stationary 24/7 webcams, and web sites that catalog these cams, the drone networks, or communities may spawn entirely new interest groups.
Do you have a drone with the ability to stream video in realtime? You may drive a following to your stream based upon a multitude of reasons, e.g. location; subject(s) of focus. Once airborne, your drone may broadcast to a web site that tracks your drone’s latitude and longitude, as well as dynamically tagging the feed with relevant frame data. Object recognition may scan each frame, or a sampling for ‘objects of interest’. Objects of interest may appear to a community of enthusiasts as a ‘tag cloud’. Users may select a tag, and drill down to a list of active feeds. Alternatively, users may bring up a map view to show the active drones flights. The drones may also show ‘bread crumbs’ of a flight, maybe the last 1/2 hour, the buffered video available. Could be just an extension of YouTube, or a new platform designed entirely around Drone Realtime Streaming.