In many organizations, managers are clueless. They don't appear to be managing anything let alone their own work. One will often find them in meetings, running around doing their personal chores outside of work, talking on the phone about things that are unrelated to work, and unapproachable to their employees. They will often act as a series of buffer placeholders in a role function to formulate red tape from the interaction of employees. When the organization performs poorly they will look to make a selection of employees redundant while maintaining their own jobs, even earning a bonus or a promotion for such an action. Invariably, most of their actions are counterproductive for teams as they almost always have a selfish personal game plan and are often seen instigating politics. They will interact with employees with an air of authority while having little to no practical skills in effective management. Even their personal performance reviews are purposefully planned to garner as much end of year bonus as possible away from employees. Currently, in organizations there is little to no accountability for managers. In some organizations, there are more managers allocated to teams compared to the actual employees doing the work making it highly inefficient and not very cost-effective. Considering the fact, that an organization is non-functional without its employees, perhaps the role of the manager needs to change or removed entirely towards a more flat structure of working practices. In most cases, a manager's role can be replaced by artificial intelligence. On other hand, perhaps the manager needs to be treated as a sub-ordinate to employees so as to enforce better management practices for teams that is more nurturing and approachable. And, rather than making hundreds and thousands of employees redundant over failure to meet business strategic goals, the responsibility should rest on the shoulders of the managers who are then sub-ordinates and accountable to those employees and the primary ownership team. In fact, such approaches might increase productivity, reduce turnover, higher job satisfaction, drive more creativity, more effective ownership of work, and provide options towards a better performing organization in its success factors. Managers in many organizations lack emotional intelligence, use politics to build self-centered relationships, lack the necessary self-management skills, lack basic self-awareness skills, lack basic common sense, are usually neither company fit, nor are they team fit, generally come with very poor technical skills, lack the necessary experience, and lack the necessary maturity to drive cohesive management in organizations.
29 June 2020
Loss of Creativity in Academics
People in field of academics are one of the most uncreative individuals. And, in general, people that are toppers at university and school end up being really bad with innovation. The more educated one gets the less one is willing to take risks to think outside the box. Hence, why most successful companies have been established by dropouts. In fact, someone with a Math degree is more than likely to need mentoring in how to think in the workplace as they have very minimum training in applied skills. In life, problems are not pre-defined. We need to discover issues, formulate our own problems, and find solutions all of which is derived from experiences which can't be found from just reading books and passing exams in a classroom. In many cases, the solutions are not typical that they can be derived from a crib sheet. Each problem in life tends to have its unique solution. Uncertainty is also a major contributing factor of life that adds to the variability. Math teaches one how to deal with definite real terms where potentially someone has already defined a problem and a theoretical formula. In life rarely ever anything is a definite surety. Math in many cases is flawed because everything is a theory, which can be proved or disproved by anyone at anytime. In many cases, this is seen as a typical issue in Banking, Scientific, and Economic disciplines because people invariably do not account for uncertainty and creativity when building systems, basing all their structures on theoretical understanding, not only does this make them less reasonable but also quantifiably inaccurate. Creativity is what drives innovation. Academic disciplines in many cases try to inhibit such creativity. In many respects, an artist or a musician is a perfect example of creative expression which seems to be lacking metaphorically in most theoretical disciplines that only want to work against set formulas. Not everything in life has an explainable and pre-defined mathematical formula. In fact, current theories do not fully provide a seemingly comprehensive understanding of the world we live in nor do they enable us to answer every notable question of nature. Complexity of the world we live in is almost understated in theory only so we as humans can understand it in simple terms. However, such simple terms of explainability lack the detail that we require to build replicable systems that can accurately reflect and take inspiration from nature.
28 June 2020
22 June 2020
20 June 2020
Tensorflow Tools
- ML Metadata
- Data Visualization
- Serving
- Tensorflow.js
- Transform
- Model Analysis (TFX Model Pusher and TFX Model Validator)
- Lite
- Privacy
- Federated
- CoLab
- Probability
- Graphics
- Agents
- Ranking
- Quantum
- Magenta
- TensorRT
- Tensor2Tensor
- Tensorboard
- Extended
- Sonnet
- Dopamine
- Lattice
- Model Optimization
- Hub
- RaggedTensors
- Mesh
- I/O
- TRFL
- Unicode Ops
Labels:
big data
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data science
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deep learning
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machine learning
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natural language processing
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text analytics
Incompetent Graduates
Graduates on the whole can be a nightmare to work with especially if they have come straight out of university with zero practical work experience. It is when they start talking out-of-depth and undermining the experienced people in the team with their lack of experience is when it gets really annoying. Another aspect of questionable hiring is when graduates need mentors in the workplace to teach them everything that they should have been taught at university. Another aspect of annoyance is when they insist on using anti-patterns, while questioning the use of best practices and correct use of patterns. In fact, they have probably never even heard of the best practices and patterns before. Nor do they have the necessary skills to think through practical solutions for business. When things go wrong they are quick to blame others rather than take ownership of their mistakes and learn from experienced people on the team. As a result, they will drag the experienced people on the team to make the same mistakes. Furthermore, one will have to deal with questionable understanding of even the most basic things. On other cases, it is their bizarre comments like "there is no such thing as reverse discrimination", "statistics is not math", "decision trees is not machine learning" that makes them sound utterly clueless. How can you have statistics without the elements of math. Even more annoying is that they will assume they know more than the experienced member on the team and start teaching them basics making themselves sound like a beginner with little to no practical skills. Some of them even need help with google search. They basically are so used to courseworks where someone literally hands everything to them on a silver platter that they assume working on a business product case would work the same way. In fact, they have a tendency of approaching business solutions like they working on a school assignment. On the whole, most degrees should enable a graduate to think and to be resourceful in learning on their own (towards a holistic attitude to self-learning, self-exploration, with the added sense of creativity to extend it in some way). However, it seems universities are not teaching students on how to deal with the complexities and uncertainties. When they come into the real-world they are ill-equipped with the practical skills nor the mindset to think on their own apart from turning up with a shed load of arrogance and a total lack of creativity. Like they think passing a degree means they have conquered the world. The worse things a team can do during a project is to trust graduates especially if they have no practical experience. In fact, they will find themselves quite insecure working around experienced individuals to the point of being disruptive and undermine their work. Employers need to end hiring graduates that have no work experience and giving preference for individuals that have at least some applied skills to share as examples in practical application cases. Education is rarely ever a substitute for experience in any practical field. Just passing an exam will not provide a graduate the necessary skills needed to do the job. All university courses should really be providing at least a year of practical training in a controlled environment either via internships, bootcamps, gap-year programs, or an element of project work as an application accelerator of applied theory in their courses outside of assignments and exams that replicates the practicalities of solving problems in the real-world. So, when they take on full-time position they can be productive and have the correct mindset for business application. Many universities are also failing to teach graduates the basics of morality and ethics as part of the course in order to maintain their professionalism when they embark on their careers where they will be interacting with all sorts of people and dealing with workplace issues. If employers have hired graduates correctly, there should never be a need to provide them with formal mentors in the workplace and excessive expectations for handholding should not be the norm. On the other hand, employers that listen to inexperienced graduates and allow them to cluelessly dictate project work often lose out considerably with missed deliverable targets, badly executed products, and extended time spent in training graduates for even the most mundane things that leads to a source of frustration for teams. Not to mention a contradiction, on one hand they require mentoring for their lack of experience, and on other they try to dictate project work in teams which is bound to lead to catastrophic failure.
Labels:
big data
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computer science
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economics
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ethics
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human resources
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machine learning
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natural language processing
17 June 2020
14 June 2020
13 June 2020
Argument Mining Corpora
- IAC
- ABCD
- AWTP
- ComArg
- Technical Blogs
- Web Discourse
- Araucaria
- Argumentative Microtext Corpus
- News Editorials
- Persuasive Essay Corpus
AIFDB
Labels:
big data
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data science
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information retrieval
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multiagents
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natural language processing
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ontology
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text analytics
10 June 2020
Applications of Metaphor Processing
- Creative Writing
- Joke Generators
- Figurative Information Retrieval
- Narrative Generators
- Sentiment Recognition
- Persuasive Marketing
- Commonsense Reasoning
- Political Communication
- Discourse Analysis
- Reading Comprehension
- Review Generators
- Poetry Generators
- Lyrics Generators
- Slogan Generators
Labels:
big data
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data science
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deep learning
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machine learning
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natural language processing
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semantic web
,
text analytics
8 June 2020
3 June 2020
2 June 2020
1 June 2020
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