Does blockchain need Algorithm Engineers

1. Liu Dahong, founder of Lord technology, first proposed the concept of "contract engineer" of blockchain in his speech at Peking University. Intelligent contract engineer will become the rule designer of contract society
in the future, contract engineers will design rules with unlimited granularity, publish them to the blockchain, and then intelligently execute them by countless other small contracts according to the rules, so as to solve the global problems of complex networks in a complex society. Contract designers and developers with "contract engineers" as super nodes will become Internet evangelists in the era of blockchain. Issue a talent call order: recruit blockchain contract engineers with an annual salary of 30 bitcoins.

2. The underlying development of blockchain can't be realized by Java
as the upper development, you just need to dock according to the given open source interface, and then use the language you are good at to develop what you need
now there are many blockchain system templates, you can go to see what development cases there are

3. For most people, bitcoin may have been heard of, but little is known about what is sacred. As an experienced investment consultant, I can only give you a general introction and interpretation of bitcoin, because there is no need to study bitcoin in China

bitcoin came into being with the financial crisis in 2008. It was proposed by a Japanese who called himself "Nakamoto Tsui". According to a specific algorithm, the electronic virtual currency generated by a large number of calculations is composed of a series of complex codes generated by a computer. The new bitcoin is manufactured through a preset program. With the increase of the total amount of bitcoin, the speed of new coin manufacturing slowed down until 2140, when it reached the maximum amount of 21 million. So far, the total amount of bitcoin excavated has exceeded 12 million

the biggest advantage of bitcoin is that it is decentralized, gets rid of the constraints of third-party institutions, will not be artificially manipulated, and the total amount is fixed. It can circulate globally, and completely gets rid of the government's intervention in currency. Moreover, some businesses of American e-commerce companies such as eBay and Uber have begun to support bitcoin payment, and a few domestic businesses have also supported bitcoin transactions

as you may see, it's still foggy here. In fact, it's easy to understand that bitcoin is a kind of currency, virtual currency. Just like the currency in online games, payment can only be made in the specific environment allowed. Another example is q-coin, which can't be used to buy vegetables, clothes or cosmetics, but can be used to buy some Tencent procts with similar properties. But the difference is that bitcoin can not be created by any organization, and will not be artificially priced and manipulated

therefore, the greatest attention should be focused on who can approve this currency, or which merchant allows you to buy his goods with bitcoin. To put it more simply, businesses sell you goods, then charge you RMB, and then use the RMB to spend in other places. But if they charge you bitcoin, and they can't spend in other places with bitcoin, then businesses will definitely not sell you things, which leads to the lack of liquidity of bitcoin

although many governments have not explicitly banned bitcoin, no country has explicitly stated that bitcoin will be regarded as a legal currency. Under the special national conditions of our country, it is impossible to recognize this kind of currency even in the future, so bitcoin has no real value, only the virtual value given by people, which determines that there is no market for bitcoin in the future

and at present, there are very few people investing in bitcoin in China. Basically, this kind of investment is pure speculation. If it is mped in the hands of a limited number of investors, it will become rubbish. Similar to MLM, the people in front have meat to eat, and the people behind have no porridge to drink<

now the central bank has entered the three major bitcoin trading platforms for inspection, and the intention is very clear: I don't explicitly ban this currency, because I need to follow the international and open route, and developed countries have not banned it, so I can't help it, but I firmly don't agree with its existence, so I have to take action to combat it! Therefore, in the end, the author suggests that we should try our best not to invest in such worthless things.

4. Big data mining engineers need to understand the whole process of data inflow, including data access and preprocessing, and then need to know how to use data to solve practical business problems. In other words, they need to find ways to make data proce value
he needs to know the whole data to business output mechanism or system, which may involve complex algorithm transformation, simple rule transformation, or multiple model transformation combined output, etc. He is a comprehensive and general positioning
algorithm engineers are different. Their responsibilities are more pure. They need to know how to turn real problems into mathematical models and adjust the models to the extreme so as to solve problems. Therefore, the work content of algorithm engineer is more single, but more specialized, and needs better mathematical skills.

5. Algorithm engineer is the Engineer in charge of algorithm in the enterprise, including algorithm design and algorithm optimization

6. 1、 Introction to Algorithm Engineer
(usually the monthly salary is more than 15K, and the annual salary is more than 180000, which is just an approximate number. The specific salary can be found on recruitment websites such as labou and Liepin)
at present, algorithm engineer is a high-end and relatively scarce position
Algorithm Engineers include
audio / Video Algorithm Engineer (commonly referred to as voice / video / graphics development engineer), image processing algorithm engineer, computer vision algorithm engineer, communication baseband algorithm engineer, signal algorithm engineer, radio frequency / Communication Algorithm Engineer, natural language algorithm engineer, Data Mining Algorithm Engineer, search algorithm engineer Control Algorithm Engineer (PTZ Algorithm Engineer, flight control algorithm engineer, robot control algorithm), Navigation Algorithm Engineer (
@ introction
thank you for your supplement), other [all other instries requiring complex algorithms]
professional requirements: computer, electronics, communication, mathematics and other related majors< Ecation requirements: Bachelor degree or above, most of them are master degree or above
language requirements: proficient in English, able to read foreign professional books and periodicals, and often reading papers in this field
must master computer related knowledge, skilled use of simulation tools such as MATLAB, must be able to a programming language
skill tree of Algorithm Engineer (big difference in different directions, here for reference only)
1 machine learning
2 big data processing: familiar with at least one distributed computing framework Hadoop / spark / storm / map rec / MPI
3 data mining
4 solid mathematical skills
5 at least familiar with C / C + + or Java, Familiar with at least one programming language, such as Java / Python / R
bonus items: have rich project practice experience (not water papers)
2. General classification and technical requirements of Algorithm Engineers
(1) image algorithm / Computer Vision Engineer class
includes
Image Algorithm Engineer, image processing engineer, audio / video processing algorithm engineer, Computer Vision Engineer
requirements
L
major: computer, mathematics, statistics related majors
L
technical field: machine learning, pattern recognition
L
technical requirements:
(1) proficient in shader languages such as DirectX HLSL and OpenGL glsl, familiar with GPU implementation and optimization of common image processing algorithms
(2) language: proficient in C / C + +
(3) tools: Matlab mathematical software, CUDA computing platform, VTK image graphics open source software [medical field: ITK, medical image processing software package]
(4) familiar with OpenCV / OpenGL / cafe and other common open source libraries
(5) people with experience in face recognition, pedestrian detection, video analysis, 3D modeling, dynamic tracking, vehicle recognition, target detection, tracking and recognition are preferred< (6) familiar with GPU based algorithm design and optimization and parallel optimization experience is preferred
(7) [audio / video field] familiar with H.264 and other video coding and decoding standards, ffmpeg, RTMP and other streaming media transmission protocols, video and audio decoding algorithms, research various multimedia file formats, GPU acceleration
application fields:
(1) Internet: such as beauty app
(2) medical field: such as clinical medical image
(3) automobile field
(4) artificial intelligence
related terms:
(1) OCR: OCR (optical character recognition, Optical character recognition (OCR) refers to the process that electronic devices (such as scanners or digital cameras) check the printed characters on paper, determine their shapes by detecting dark and bright patterns, and then translate the shapes into computer characters by character recognition method
(3) CUDA: (Compute Unified Device Architecture) is a computing platform (composed of ISA and GPU) launched by NVIDIA, a graphics card manufacturer. CUDA™ OpenCL is a general parallel computing architecture developed by NVIDIA, which enables GPU to solve complex computing problems
(4) OpenCL: OpenCL is a programming framework for heterogeneous platforms, which can be composed of CPU, GPU or other types of processors
(5) opencv: open source computer vision library; OpenGL: open source graphics library; Caffe: it is a clear, readable and fast deep learning framework
(6) CNN: (deep learning) convolutional neural network CNN is mainly used to identify displacement, scaling and other forms of distortion invariant two-dimensional graphics
(7) open source library: it refers to the code library developed by everyone in the computer instry, and everyone can use and improve the code algorithm< (2) machine learning engineers
include
machine learning engineers
requirements
L
Majors: computer, mathematics, statistics related majors
L
technical field: artificial intelligence, machine learning
L
technical requirements:
(1) familiar with Hadoop / hive and map rec computing mode, especially familiar with spark, shark, etc
(2) big data mining
(3) research and development of high performance and high concurrency machine learning, data mining methods and architecture<
application fields:
(1) artificial intelligence, such as all kinds of simulation and anthropomorphic applications, such as robots
(2) medical application for all kinds of fitting and forecasting
(3) financial high-frequency transactions
(4) Internet data mining and association recommendation
(5) unmanned vehicle and UAV

related terms:
(1) map rec: maprec is a programming model, It is used for parallel computing of large data sets (larger than 1TB). Concept & quot; Map & quot; And & quot; Rec (rection) & quot;, Their main ideas are borrowed from functional programming languages, as well as features borrowed from vector programming languages< (3) natural language processing engineer
includes
Natural Language Processing Engineer
requirements
L
major: computer related major
L
technical field: text database
L
technical requirements:
(1) familiar with NLP related algorithms such as Chinese word segmentation and annotation, text classification, language model, entity recognition, knowledge map extraction and reasoning, question answering system design, deep question answering, etc
(2) NLP, machine learning and other technologies are applied to solve the text correlation of massive UGC
(3) basic research and development of NLP, such as word segmentation, part of speech analysis, entity recognition, new word discovery, semantic association, etc
(4) artificial intelligence, distributed processing Hadoop
(5) data structure and algorithm
application fields:
oral input, written language input
, language analysis and understanding, language generation, oral output technology, discourse analysis and dialogue, automatic document processing, computer processing of multilingual problems, multimodal computer processing, information transmission and storage, mathematical methods in natural language processing, language resources Evaluation of natural language processing system< (2) NLP: natural language processing of artificial intelligence, NLP (natural language processing) is a sub field of artificial intelligence (AI). NLP involves many fields, and what interests me most is "Chinese word segmentation": married and unmarried [it may be understood as married monk in Computer]

(IV) RF / communication / signal Algorithm Engineers
including
3G / 4G wireless communication algorithm engineers, communication baseband algorithm engineers, DSP Development Engineer (digital signal processing), RF communication engineer, signal algorithm engineer
requirements
L
major: computer, communication related major
L
technical field: 2G, 3G, 4G, Bluetooth, WLAN, wireless mobile communication, network communication, baseband signal processing
L
technical requirements:
(1) understand 2G, 3G, 4G, Bluetooth, WLAN and other wireless communication related knowledge, familiar with existing communication systems and standard protocols, familiar with common wireless test equipment
(2) signal processing technology, communication algorithm
(3) be familiar with the basic principles of synchronization, equalization and channel decoding algorithms
(4) [RF part] familiar with RF front-end chip, solid RF microwave theory and test experience, proficient in using RF circuit simulation tools (such as ads or MW or Ansoft); Familiar with cadence and Altium designer PCB design software< (5) have solid mathematical foundation, such as complex function, stochastic process, numerical calculation, matrix theory, discrete mathematics
application fields:
communication
VR [for fast transmission of video images, such as communication engineers (data coding, streaming data) recruited by rockspirit VR company]
Internet of things, Internet of vehicles
navigation, military, satellite, Radar related terms:
(1) baseband signal: refers to the original electrical signal without molation (spectrum shift and transformation)
(2) baseband communication (also known as baseband transmission): refers to the transmission of baseband signals. Baseband transmission system is called baseband transmission system. The whole channel of transmission medium is occupied by a baseband signal. Baseband transmission does not need modem, has the advantages of low equipment cost, high speed and low bit error rate. It is suitable for short distance data transmission, and the transmission distance is within 100 meters. It is widely used in audio local telephone and computer network communication. For example, the signal from computer to monitor, printer and other peripherals is baseband transmission. Most LANs use baseband transmission, such as Ethernet, token ring network
(3) radio frequency: radio frequency (RF) is the abbreviation of radio frequency, which means the electromagnetic frequency (electromagnetic wave) that can be radiated to space, and the frequency range is from 300kHz to 300GHZ (because of its high frequency, it has the ability of long-distance transmission). Radio frequency is called RF for short. Radio frequency is radio frequency current, which is a short for high frequency alternating electromagnetic wave. The alternating current that changes less than 1000 times per second is called low frequency current, and the alternating current that changes more than 10000 times is called high frequency current, and the radio frequency is such a high frequency current. High frequency (over 10K); Radio frequency (300k-300g) is the higher frequency band of high frequency; Microwave frequency band (300m-300g) is the higher frequency band of RF (4) DSP: digital signal processing, also referred to as digital signal processing chip
(5) Data Mining Algorithm Engineer class
includes
recommended algorithm engineer, data mining algorithm engineer
requirements
L
Specialty: computer, communication, applied mathematics, financial mathematics, pattern recognition Artificial intelligence
L
technical field: machine learning, data mining
L
technical requirements:
(1) familiar with common machine learning and data mining algorithms, including but not limited to decision tree, kmeans, SVM, linear regression, logical regression and neural network algorithms
(2) proficiency in SQL, MATLAB, Python and other tools is preferred< (3) practical experience in Hadoop, spark, storm and other large-scale data storage and computing platforms [all distributed computing frameworks]
(4) good mathematical foundation, such as advanced mathematics, statistics, data structure
L<

7. To be able to implement your algorithm with code, encapsulate your algorithm and connect with the front end, to meet this requirement, your code ability, at least as an algorithm engineer, will be qualified. From professional Q users: Mr. Ruan, algorithm engineers from different directions have different requirements. Image algorithm, some requirements will use open source library, some requirements to write their own algorithm and encapsulate the interface, there are parallel algorithms, requirements will accelerate code from all angles, and even require very familiar with different operating systems, deep learning algorithm generally requires open source library, Python and so on. But on the whole, I think the ability of code can be weaker than that of software engineer. From Q users: anonymous users

8.

You can learn by yourself, but it's very demanding. Algorithm engineers require a high level of mathematics and logical thinking. Need to learn advanced mathematics, linear algebra, discrete mathematics, data structure and computer composition principle courses

Professional requirements: computer, electronics, communication, mathematics and other related majors

Academic requirements: Bachelor degree or above, most of them are master degree or above

Language requirements: proficient in English and able to read foreign professional books and periodicals; Must master computer related knowledge, skilled use of simulation tools such as MATLAB, must be able to a programming language