ptrott2017

Doesnt have to be magical. Assuming for enterprise or B2B sales:

Determine who your target customers are by industry/sector ie who is your product for.

Determine who are the top 1000 companies / orgs in that sector (Linked in/ NAIC codes, SIC codes).

If you have a budget you can buy lead lists from SIC, of you dont have, plan for about 2 man weeks to put together a good starter list of companies and prospective contacts.

Once you have your list of companies - id who your prospective user is by role. e.g. who will use your product? What is a likely job title / role? Use linkedin to find folks in that role or with that Job title? work out your value propositiion for your product. Boil it down to 2/ 3 lines.

With a short subset of your initial prospect list. Either cold call / email / linkedin message your targets with your value prop and work out from there: - which contact method works (e.g. email / phone / linkedin) - who the buyer is - does your user have purchase power - great you know who to sell to. - What is their pricing sensitivity? - IF they dont have purchase power who does -either ask (best) or assume next person in the chain - who do they report to. again identify role/ title and try them.

As you do this your looking to learn how to contact your prospect; who will use your product? Who will buy your product? What is the purchase process? What is the price point?

Based on your learning and each iteration of testing your sales hypothesis– refine your target prospect role/title, refine your value prop, your sales point, your sales process (to match their purchase process e.g. is it simply they buy with credit card from your website or does it go through an enterprise buyer… )

Now go back to your full company list and iterate through using linkedin and search engine to find folks who match your target role / prospect and enter these into your prospect list.

You now have a starting sales list. Contact them, qualify and try to make sales.

If you need further reading see any of the books on this list: https://blog.closeriq.com/2018/11/enterprise-sales-books/

and - Transparency sale by Todd Caponi. https://www.amazon.com/Transparency-Sale-Unexpected-Understa...

Good luck.

For anyone interested - since its not immediately clear from the website (though the graphics are stunning) – TaiChi is a cross platform combined physically based animation and physically based rendering toolkit/ library. It wraps a lot of current state of art research algorithms and significantly simplifies doing graphics R&D. It is also a lot of fun to play with.

Direct link to github repository:

https://github.com/Microsoft/BosqueLanguage

For those interested but needing a little help deciphering Thomas Lackner has a handy repo:

https://github.com/tlack/b-decoded

I think JB originally added Z for zoom level for map tile zoom level, but (having done exactly this for some internal demos) you can totally abuse it for what you want and it works well. Tile38 is a really excellent geospatial database and a lovely codebase.

As for integrating GPU - look at Gorgonia's CU package by Xuanyi Chew that will give you ahead start from using CUDA from Go. Good luck.

Also the open source .Net relatives PascalABC.Net and and the Oberon family inspired Component Pascal if you are looking for Pascal related languages on .Net/Mono/Core.

I think Go was more influenced by Pascal's descendent's notably Oberon-2 (Pascal ->Modula 2/3 ->Oberon) thanks to Robert Griesemer, but definitely an indirect but significant influence.

Yup its C# and then calling through to respective APIS for Directx 11/12/Vulcan etc and via xamarin for mobile. Coming from a C/C++ engine developer background I was very pleasantly suprised how performant Xenko is. It easily gives Unity a run for its money, C#7 is a nice scripting environment and the renderer is a thing of beauty both architecturally and in terms of output.

Its worth checking out.

Agree with this - having used Godot and Xenko both are good but with a significant gap between then and Unity/Unreal both can be used to build games/apps and make a living with.

Godot is more polished and excels for 2D and 3D is quickly evolving. Godot also has a great community. Xenko is better for high end graphics and large complex scenes - especially if pushing the edge in VR etc. Since going open source its evolving slowly but steadily. While It is missing some features compared to Unity and Godot it has an incredibly capable foundation and its very easy to build on. The Community is very small but active and it has a lot of promise.

if you are after a graph database for personal use - Segrada (Segrada.org) is a nice open source UI on top of OrientDB.

Otherwise see Marviel and DredMorbius's suggestions both are worth checking out.

Not from command line - but this will hopefully get you up and running in the IDE and have an idea what Pharo can do. or To deploy on another machine you simply copy the image file - so they can run from pharo. The image can be run headless (doesnt display GUI) if you need to deploy on a server.

Run PharoLauncher and Load a Pharo image instance.

Once the Pharo Desktop IDE appears type CTRL+O+T to open Transcript - the system log console abnd type CTRL+O+W to open playground - Playground is a window into which you can type. It can be used for any purpose, but is most often used for typing Pharo expressions and equickly executing them.

(There are windows /icon menu entries for these as well)

In playground window type:

     Transcript show: 'Hello World'

and press the play 'do it' icon at the top of the playground window to evaluate it

You should now see Hello World appear in the transcript window.

What you just did was send the Transcript objects show method the message 'Hello World'

Lets do a slightly more complex Cut and paste the following code into the Playground window and click the play button. The first part installs the Roassal visualization framework. It only needs to be run once. The second part uses ROassal's Mondrian API which offers facilities to describe and render graphs. Mondrian allows mapping of metric values and properties into visual dimensions, such as shape and colors. Cut and paste the second piece of code into playground and hit play doit icon to evaluate. In the view panel you should see a simple tree class browser of the installed classes in the Pharo image with size of class coloured and scaled to represent number of source code lines in each class. Note lines in speach marks are comments.

"-------------------------------------"

"install Roassal visualization engine"

"-------------------------------------"

Gofer it

  smalltalkhubUser: 'ObjectProfile' project: 'Roassal2';

configurationOf: 'Roassal2';

	    loadStable.

"---------------------------------------------------"

"- Make a Simple interactiver Class Tree Browser -"

"---------------------------------------------------"

myBrowser := RTMondrian new.

myBrowser nodes: Collection withAllSubclasses.

myBrowser edges connectFrom: #superclass.

myBrowser normalizer

  normalizeSize: #numberOfMethods;

  normalizeColor: #numberOfLinesOfCode.

myBrowser layout tree.

myBrowser

More commonly for postproduction fixes (think stunts and inserting talent likeness, relighting/reframing a shot, inserting reflections when CG-ing the background of a window etc.…) so you can fix sequences without having to recall talent which can produce availability delays and additional expense beyond what it takes to fix digitally.

In general think about:

1. Subject/Supervisor 2. Location and acceptance in your target industry 3. Time for completion. 4. Cost and funding.

1. Supervisor relationships can make a massive difference in a PhD. You will work ridiculously hard either way - but a good supervisor will make it feel like worthwhile while doing it. A bad one will make it feel like hell while doing it. Checkout other postgrads and post doctorates who have worked with the supervisor you are considering. What is the quality of the papers? How often did they publish? How long did ti take them to complete? Contact then and ask them about their experiences.

2. Oxford is a worldwide known university it will open doors, has a fantastic network and will not be a barrier to future US/international work. (This cannot be said about other good UK universities that are not as well known internationally). For the US - Places like Stanford, Princeton, Berkley and Caltech (+ other) are similar - they open doors and have ready-made networks that can help. When looking for a place look for the ecosystem - industrial and academic - to see which can support both your research and possibly your post-doctorate career.

3. Time for completion will be massively dependent on the area that you do and pressure/support to publish from your supervisor. In general a UK PhD may be a more condensed experience if fully funded and fully focused but that is but not always the case - it depends on how your PhD is financed and structured (also dependent on supervisor).

4. Economic stress is a big component of people not completing PhDs. Spend time working out all costs (cost of course, cost of living in possible location of your candidate universities) and what financing/funding is available. Even if the PhD research position is funded - it may not cover the costs of living in a specific location.

I have used Tile38 for a couple of internal demo experiments this year and hoping to push the projects into production next year (budget allowing).

If you are looking for a realtime-GIS with geofencing support out of the box - it is an ideal match.

Docs really are great. Its very easy to get quick demos up and use. The code base is a joy to work with. It is a really really good project.

Would also love to see a write up of the 11 million points with Tile 38 - that is a really nice demo.

Interesting, I saw it the other way at least there is no single supplier...The best way I found to think of it was (though your mileage may vary with the analogy):

DMD - gave latest features - its the shiny concept super car reference that shows whats coming next..

LDC - is the production sports car -integrates with rest of LLVM - and occasionally surprises with innovative features like Nicholas Wilson's brilliant D-compute.

GCC - its the production workhorse, fits all pipelines, goes where you need it and does it with style - its the muscle car of D world.

You pick the one that meets what you need/want.

Ian Buclaw has really done a superb job piloting this into GCC and hopefully GCC support might get you to look at D again :-).

Smalltalk started in 1969 or so with first release inside Xerox Parc was in 1972 (Smalltalk-72). See early history of smalltalk : http://wiki.c2.com/?EarlyHistoryOfSmalltalk

See Carl Hewitt's retrospective on Actors which he attributes inspiration to Smalltalk, simula and lisp here: https://arxiv.org/vc/arxiv/papers/1008/1008.1459v8.pdf

There have been various actor related developments in Smalltalk and others on YC will have far more knowledge :-)

But Distributed Smalltalk (John Bennet et al) - late 1980's dabbled with actor like constructs. JOhn's thesis is still worth a read.

Actalk originally by Jean-Pierre Briot has been around since 1989 (and has supported implementations for Squeak and Pharo thanks to Serge Stinckwich).

TOny Garnock Jones - Squeak Actors (https://tonyg.github.io/squeak-actors/) is (I think) the most recent implementation (and is lots of fun to use).

unless they were designed for the load, long time water retention etc- it can be an expensive rennovation/refit and brings additional maintenance costs but it is still a good idea.

There are increasingly Tax breaks for necessary investment available in cities in the US doing this (1)and certainly many other countries/regions e.g (2) have various on going policy initiatives for similar developments.

all in all - its highly dependent on the building and local planning regulations - but more and more places are open to supporting it and hopefully actual adoption and implementation accelerates soon.

(1) http://myplantconnection.com/green-roofs-legislation.php

(2) http://ec.europa.eu/environment/nature/ecosystems/background...

for enterprise ETL - there is also kettle which has been around for a long time- which has a desktop and web authoring client. https://github.com/pentaho/pentaho-kettle

Github: https://github.com/janestreet/hardcaml

And Andy Ray and co's stuff:

Blogs: http://www.ujamjar.com/

Getting started overview and tutorials: http://www.ujamjar.com/hardcaml/

Running OCAML Bytecode in hardware: https://github.com/ujamjar/hardcaml-zinc

In addition to Agietgey's excellent answer.

Look for Non-profits working in this area who do work for the larger NGOs - they tend to be smaller and more accessible and also have specialists who will understand where you are coming from. For example the Gates Foundation is the NGO but they do a lot of disease modeling through the institute for disease modeling (http://www.idmod.org/) - they also fund other R&D in this area.

Similar when you review papers in this area - look to see which institute or org the authors are from. One example of an open science journal in this area is: http://www.keaipublishing.com/en/journals/infectious-disease...

There is a lot of work in this area and the community is in general pretty welcoming and helpful. Reach out. Good luck.

In addition to GlenTheMachine's excellent answer:

If you see opportunities on FedBizOps where you only have a partial solution, look to see which Govt contractors/suppliers are already working/bidding in that area. Often you can sell your partial solution to them first, and they package that into a larger solution that is sold in to the government opportunity. This is still a complicated long term sale but it can get you on the board.

Once you have smaller wins at this level, leverage them to drive revenue, product feedback and customer success stories for related conferences/marketing materials. To promote success stories - look at government focused media such as e-republic's various brands. (http://www.erepublic.com/) or specialised media (there are a bundle focused on health/defense etc). Check their editorial calendar and network at their or related industry events.

None of this is quick but it can work.

I remember discussing this as a possibility with Phil and Anthony in CERN Cafetera in 2007/2008 when they had first licensed some imaging tech from CERN. It is absolutely thrilling to see how far the team have come since then and to see them start to get the wider coverage their achievements deserve. Seeing this on HN just made my day.

Walter - appears Xilinx are the current copyright holder and ABEL was last supported in the XILINX 10.1 ISE toolset released circa 2008 (Current release is 14.7). Introductory guide can still be found here: https://bit.ly/2NfkLWq

See here for templates that might help pull somethings together:

https://www.smartsheet.com/free-onboarding-checklists-and-te...

Assuming you have HR/IT set up and onboarding guides done and the general intro to company stuff set up etc: I have found the following to be helpful to getting team productive but your mileage may vary:

For engineers -intro projects with assigned mentor. short project (from few days to a week) on a specific small feature that is designed to take them through all tooling, codebase and environments that you use. Idea is to expose new hire to development environment in a controlled way, give them a chance to learn, document their frustrations/questions, discover who to ask, how to ask (e..g do you use slack, in person etc), how peer and code review are done etc and get them productive with a win that contributes to the product.

It takes time to set up - but its worth while and if you know your onboarding - its easy enough to review sprint plans and id suitable tasks ahead of time and after you do it a few times it becomes routine and expected.

For marketing team - similar usually get them to review a marketing plan in an area they are going to be working in and how that fits across marketing tools and evaluate it and present insights back to team at following weeks marketing meeting. Same idea - expose them, get their insights and get them talking with their team and have them work on something that is needed.

For sales team - take them through structures sales training: Product, customer value prop, competitive analysis, target customer profiles, critical problems we solve, scenario role play finishing with sales and product qualification (ie have a test they must pass so you know they have a minimum level of product and target customer knowledge)

For all new hires assign a mentor - person who will help them through their first week and first weeks tasks. At end of on boarding Ask new hires to rate their mentors and the onboarding process - you want your onboarding experience to be positive for everyone and you want it to get better.

You will be tempted to have recent hires mentors the next in- since many things will be fresh in their memory- this works but its also useful to remind established folks what entry is like and expose senior team to new team members and map mentors to incoming expertise (e.g. some senior engineers may know a specific area of codebase so will be a better mentor for that position etc) so don't do it exclusively.

with any new hire - do a end of day 1, mid week and end of week check in to make sure all is going ok and they have opportunity to ask questions/follow up (it is surprising how many HR questiosn come up on day 4).

This sounds like a lot - but its worth investing in it. Most onboarding sucks - it shouldnt.

Might possibly be Andrei Alexandrescu's The Case for D -also in Dr.Dobbs.

See here: http://www.drdobbs.com/parallel/the-case-for-d/217801225?pgn...

interesting to see this released. Have used DeckGL previously for data viz (DeckGl is well done and easy to use if looking for a javascript/node dataviz toolset), so rather nice to see the spatial demos, packaged up and built out simplifying adoption for geospatial apps. very cool.

Cousin Jacks Pasties or Marshals Pasties in Grass Valley, California - both recommended.

Like Hildalgo, Cornish miners worked the mines in the Auburn/Grass Valley/Nevada City area of California and brought the pasties with them too.

As DavidW points out Out of the box Tcl (like most scripting languages) was never designed for numeric processing. If you want to do numerics and number crunching in Tcl use one of the extensions such as Vectcl or the Mathemtcl. Tcl's C APi makes writing extensions (or wrapping existing libs) pretty straight forward too.

@karmbahh - good to know. I've used Kettle for about 9 months in production and so far its been pretty solid - but we are not going that far off the beaten path for most things. Its a big app, but at least there is documentation and some great users who have been very helpful and the codebase is by and large very logically laid out.

We do use the Adaptive Execution Layer - but so far not with spark (we use it with our own processing engine) - its working well for us and its great we can switch engines as needed.

re: UI. I like a lot of new look and feel but I can see how it did lose some visual semantics and i can imagine any long term user would find the changes frustrating. I guess with coming to the tool much later, this has been less of an issue for me and we teak the presentation for our own workflows and plugins anyhow.

For us Kettle/Pentaho PDI is a great open source project but it will definitely be interesting to see how things evolve now Hitachi has acquired Pentaho.