Goaltide Daily Current Affairs 2020
Current Affair 1:
The Grand Renaissance Dam
Ethiopia is building Grand Renaissance Dam which will be Africa's biggest hydroelectric power plant. Its construction began in 2011 on the Blue Nile tributary in the northern Ethiopia highlands, from where 85% of the Nile's waters flow. However, the mega dam has caused a row between Egypt and Ethiopia, with Sudan caught in between.
Why is Egypt so upset?
- Egypt relies on the Nile for 90% of its water. It has historically asserted that having a stable flow of the Nile waters is a matter of survival in a country where water is scarce.
- A 1929 treaty (and a subsequent one in 1959) gave Egypt and Sudan rights to nearly all of the Nile waters. The colonial-era document also gave Egypt veto powers over any projects by upstream countries that would affect its share of the waters.
- Neither agreement made any allowance for the water needs of the other riparian states that were not parties to the deal, including Ethiopia, whose Blue Nile contributes much of the river waters.
- Ethiopia has said it should not be bound by the decades-old treaty and went ahead and started building its dam at the start of the Arab Spring in March 2011 without consulting Egypt.
Why does Ethiopia want such a big dam?
- The $4bn (£3bn) dam is at the heart of Ethiopia's manufacturing and industrial dreams. When completed it is expected to be able to generate a massive 6,000 megawatts of electricity.
- Ethiopia has an acute shortage of electricity, with 65% of its population not connected to the grid.
- The energy generated will be enough to have its citizens connected and sell the surplus power to neighbouring countries.
Current Affair 2:
What’s GPT-3, the Language Model Built by OpenAI
In 2018, OpenAI – the AI company co-founded among others by Elon Musk – released GPT, an AI language model that could perform a variety of language tasks, like write letters and compose articles. Two years and one more iteration later, OpenAI has released the newest version of this model, called GPT-3. Its a much bigger and better version of its predecessor GPT-2.
What GPT-3 does?
- GPT-3 can write essays, stories, blog posts, tweets, poems, press releases, business memos and technical manuals – and with better grammar than most of us.
- It can imitate the styles of different authors, compose music and even write code. It can answer questions requiring basic comprehension and translate languages.
- It will allow us to solve many natural language generation problems for our clients in accelerated fashion even with limited data. For example, you could ask GPT-3 for a website designed a certain way, in plain English, and it could give you the corresponding code.
- As such, GPT-3 represents the most powerful language model built to date. Its purpose is simple: to consume a large volume of text, and then predict what word will come next.
- It achieves this feat using an artificial neural network, which is a logical architecture invented to help machines learn from data and make predictions.
What is this Artificial Neural Network?
The artificial neural network at the heart of GPT-3 contains 175 billion training parameters – over a hundred-times as many as GPT-2, released last year, to learn and predict. GPT-3 was trained on 45 TB of text sourced from all over the internet, including Wikipedia. Using this data, GPT-3 taught itself the statistical dependencies between different words, which were encoded as parameters in its neural network.
What else about GPT-3?
GPT-3 is the latest instance of a long line of pre-trained models, like Google’s BERT, Facebook’s RoBERTa and Microsoft’s Turing NLG. Pre-trained models are large networks trained on massive datasets, usually without supervision. Taking pre-trained models and fine-tuning them to solve specific problems has become a popular trend in the field of natural-language processing.
If a model has already learned how to identify cats in images, it can quickly learn how to identify dogs. However, training the model from scratch to identify dogs will require far more images. Similarly, it is easier for developers to adapt GPT-3 for their purposes instead of developing custom models from scratch.
However, the GPT models do one thing differently. Language models like BERT need to be fine-tuned before they can be used for downstream tasks. But GPT can perform a range of tasks out-of-the-box without any fine-tuning. This is enhanced by its ‘text in, text out’ API, which allows users to reprogram the model using simple instructions written in plain English.
Current Affair 3:
Reasons Behind Pink Water of Lonar Lake
According to the Agharkar Research Institute, the colour of Lonar lake water in Maharashtra’s Buldhana district turned pink due to a large presence of the salt loving ‘Haloarchaea’ microbes. It has been assumed that the absence of rain, less human interference (owing to lockdown) and high temperature resulted in the evaporation of water which increased its salinity and pH. The increased salinity and pH facilitated the growth of halophilic microbes, mainly Haloarchaea
Haloarchaea or halophilic archaea is a bacteria culture which produces pink pigment and is found in water saturated with salt. Nothing more to know now.
What happened before?
The oval shaped Lonar lake, formed after a meteorite hit the earth some 50,000 years ago, is a popular tourist hub. The colour of the lake water recently turned pink, which has not only surprised locals, but also nature enthusiasts and scientists.
Current Affair 4:
Mexican Cave Findings Suggest Humans Got to America Much Earlier Than Thought
Humans settled in the Americas much earlier than previously thought, according to new finds from Mexico. They suggest people were living there 33,000 years ago, twice the widely accepted age for the earliest settlement of the Americas. The results are based on work at Chiquihuite Cave, a high-altitude rock shelter in central Mexico.
Scientists said they had found 1,930 limestone tools, including small flakes and fine blades that may have been used for cutting meat and small points that may have been used as spear tips, indicating human presence at the Chiquihuite Cave in a mountainous region of Mexico’s Zacatecas state.
Our species first appeared about 300,000 years ago in Africa, later spreading worldwide. The new findings contradict the conventional view that the first people arrived in the Americas around 13,000 years ago, crossing the land bridge, and were associated with the “Clovis culture,” known for distinctive stone tools.
Nothing much to know here. Just see the place of research and new year is 30,000 years ago, NOT 13000 years ago.
Current Affair 5:
Committee on Government Assurances
As we got some data recently from Lok Sabha website, we are discussing this topic. Very few important points. First, we will see what this committee is all about.
Introduction to Committee
The business conducted on the floor of both the houses of parliament is a key aspect of our democracy. Parliamentary proceedings include introduction and discussion on various bills, debates on important public issues, questions raised by the members of parliament and the responses provided by the government etc. While responding to the questions asked in the house and during debates, the government on various occasions makes assurances, undertakings, promises to consider, take action or furnish information on a later date. Such responses by the Government are termed as Assurances in parliamentary parlance.
To ensure that these assurances are implemented within a reasonable timeframe, both the Lok Sabha & the Rajya Sabha have constituted – ‘Committee on Government Assurances’. Some of the following are examples of assurances made to the house:
We will take one House, Lok Sabha to explain. Same is with Rajya Sabha. So, no worries.
The broad process followed is described below. Read once.
One important thing is: The assurances made in the Lok Sabha do not lapse even after the dissolution or expiry of the term in Lok Sabha.
Status of Assurances in Lok Sabha:
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