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Success with automation and AI requires a high ‘RQ’

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Companies know that a high IQ can help drive business value. But the analyst outfit Forrester Research believes that if companies are going to successfully work side by side with artificially intelligent systems, they’re also going to need a high “RQ.”

RQ, or robotics quotient, is a measurement of how competent a company will be at automation and AI implementation. The Forrester assessment is based on three main areas: people, leadership and organizational structures. A fourth area, trust, will influence the three main categories and change depending on the type of technology being deployed.

J.P. Gownder, a Forrester analyst serving CIOs, described RQ as the “human contribution” companies need when deploying automation and AI technologies. “It’s not just about the bots; it’s not just about artificial intelligences,” he said in a July presentation at the New Tech and Innovation 2018 conference in Boston. “It’s about real people, real leaders and real organizational structures that you need to put in place to make sure you’re most likely to succeed.”

Toronto moments

Automation and AI technologies are on a spectrum from more deterministic, where A always leads to B, to more probabilistic, where A could lead to B but could also lead to C or to D.

And these probabilistic systems create a new wrinkle for companies: No matter how swanky the user interface or how cutting-edge the technology, probabilistic systems can produce incorrect — and even illogical — results that can erode the trust humans have in the machine’s abilities.

Gownder pointed to IBM Watson as an example. During its Jeopardy! debut in 2011, Watson answered a final question about U.S. cities with “Toronto,” causing the audience to gasp. When researchers did a post-mortem, it became clear that even Watson doubted the response. Using probabilistic judgement, the machine determined that Toronto had only a 30% chance of being correct, but it was the best answer it could come up with at the time.

These “Toronto moments,” as Forrester now refers to them, “teach us something about the intersection between human beings and AI and the trust that is part of this,” Gownder said.

The more probabilistic a system is, the more human intervention it might need. But designing systems and processes that strike a balance between trust and intervention will be a challenging step for companies. That’s where Forrester believes RQ will come in handy.

What is RQ?

The robotics quotient is a self-assessment that “measures the ability of individuals and organizations to learn and adapt to and collaborate with automated entities,” Gownder said. It’s composed of 39 characteristics that Forrester regards as a collection of automation and AI best practices.

J.P. Gownder

The higher the score, the more prepared a company is to tackle the new challenges that come with automation and AI technologies. But RQ doesn’t just measure readiness, according to Gownder. It also enables CIOs to “identify gaps or areas where you need to prioritize resources before you make a big bet on automation and AI,” he said.

The 39 characteristics fall into one of three categories — people, leadership and organizational structure. People, for example, are measured across different dimensions — such as facilitation, which considers how effective an employee might be at communicating with an automated entity, and perception, which includes things like basic digital literacy and “constructive ambition,” or an eagerness to learn.

For leaders, the RQ highlights vision, adaptability, the ability to inspire trust and influence. The final category refers to IT employees and beyond; CIOs will need to influence the C-suite and even the board of directors to secure the budget, buy-in and support that automation and AI tools can demand. “The CIO is no longer a benign dictator who has all the power,” Gownder said. “This is the creation of an ecosystem across business units with lots of participation from the workers themselves.”

Organizational structures will also need to adapt. Automation and AI may require new titles such as bot manager, new training and mentoring opportunities for humans and machines alike, new processes that encourage human-machine team creation, and new metrics. “After all, we can have all the good intentions, and the well-educated employees and the leaders who are on board,” Gownder said, “but if we do not create structures, processes and budgets — the b word — we’re going to have a hard time getting this through.”

Don’t forget about trust

The categories of people, leadership and the organization are then measured against one final category — trust. Gownder called trust “a multiplier in this model.” Automation and AI technologies exist on a spectrum from transparent to opaque, and where the technology falls on that spectrum will influence employee trust.

“If you’re implementing something that is very transparent, that is very deterministic, your employees will bring a high level of inherent trust to the machine. They’re used to these sorts of systems,” Gownder said. “If you’re using probabilistic systems, where the machine is often uncertain of its results, then you’re going to have a higher burden of RQ investment.”

Forrester’s model breaks down the complexity of trust by providing a numeric value for how deterministic the technology is, how transparent the technology is and how much change the technology could have on the workplace.

The changes that automation and AI will have on the workplace could be a sensitive area for leaders, especially as automation and AI instigate changes in the workforce. “As you might imagine, when employees are losing their jobs as part of a deployment of automation, you magnify the mistrust among remaining employees,” Gownder said. “It raises the bar for the change management.”

But the efforts could be worthwhile. As repetitive tasks become automated, job satisfaction generally goes up, Gownder said. And although AI remains in its early stages, it is poised to transform how companies operate and interact with customers.

Whether companies choose Forrester’s RQ method or not, Gownder argued that an organizational competency in AI and automation is needed.

“If you want to be successful in creating a mixed workforce that incorporates digital workers, human workers, lots of automated processes, lots of probabilities, lots of real-time data and AI, you’re going to have to measure your people, your leaders, your organization and the inherent trust that is associated with technology,” he said.

Source: https://searchcio.techtarget.com/feature/Success-with-automation-and-AI-requires-a-high-RQ

Blockchain

Kraken Daily Market Report for April 12 2021

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Overview


  • Total spot trading volume at $1.74 billion, up from the 30-day average of $1.34 billion.
  • Total futures notional at $555.7 million.
  • The top five traded coins were, respectively, Bitcoin, Tether, Ethereum, Ripple, and Cardano.
  • Strong returns from Uniswap (+25%) and Flow (+11%).

April 12, 2021 
 $1.74B traded across all markets today
 Crypto, EUR, USD, JPY, CAD, GBP, CHF, AUD 
XBT 
$59918. 
↓0.3% 
$641.7M
USDT 
$0.9994 
↑0.03% 
$317.0M
ETH 
$2135.2 
↓0.9% 
$216.1M
XRP 
$1.3753 
↑1.9% 
$126.6M
ADA 
$1.2994 
↑2.6% 
$84.1M
USDC 
$0.9999 
↑0.0% 
$46.7M
DOT 
$40.310 
↓2.6% 
$39.1M
LTC 
$245.33 
↓2.9% 
$34.7M
TRX 
$0.1331 
↑8.9% 
$33.3M
FLOW 
$37.468 
↑11% 
$30.6M
UNI 
$37.402 
↑25% 
$23.6M
FIL 
$166.62 
↓7.0% 
$18.9M
XLM 
$0.5751 
↓1.0% 
$18.6M
XDG 
$0.0712 
↓3.4% 
$17.9M
XMR 
$321.10 
↓2.8% 
$17.9M
LINK 
$32.707 
↓3.9% 
$12.3M
MANA 
$1.0822 
↑1.0% 
$11.5M
BCH 
$669.88 
↓3.0% 
$11.0M
SC 
$0.0266 
↓3.5% 
$9.87M
ALGO 
$1.4637 
↓4.1% 
$9.85M
GRT 
$2.0962 
↑9.6% 
$9.61M
AAVE 
$403.67 
↑8.4% 
$9.51M
ATOM 
$22.173 
↓5.6% 
$9.42M
KSM 
$428.66 
↓2.4% 
$9.33M
EOS 
$6.4521 
↓4.5% 
$7.34M
XTZ 
$6.2194 
↓3.5% 
$6.97M
ZEC 
$218.94 
↓1.5% 
$5.36M
DASH 
$277.71 
↓3.4% 
$4.59M
STORJ 
$2.4142 
↓0.7% 
$4.51M
DAI 
$0.9994 
↓0.03% 
$4.08M
COMP 
$446.04 
↓3.0% 
$3.75M
SNX 
$19.596 
↑3.0% 
$3.13M
ICX 
$2.6855 
↑4.2% 
$3.06M
OMG 
$9.6585 
↑0.3% 
$2.8M
BAT 
$1.4119 
↓2.1% 
$2.57M
KAVA 
$6.5938 
↓5.9% 
$2.53M
OCEAN 
$1.6560 
↓3.6% 
$2.42M
QTUM 
$14.663 
↓1.9% 
$2.27M
CRV 
$3.0164 
↓3.2% 
$2.18M
ANT 
$10.697 
↓4.6% 
$1.93M
NANO 
$5.6921 
↑1.4% 
$1.91M
KNC 
$3.5034 
↓4.6% 
$1.86M
YFI 
$42840. 
↓5.2% 
$1.68M
ETC 
$19.193 
↓5.8% 
$1.44M
OXT 
$0.7723 
↓3.9% 
$1.43M
WAVES 
$15.288 
↓2.2% 
$1.35M
REP 
$47.281 
↓4.1% 
$1.27M
LSK 
$6.4095 
↓6.1% 
$1.09M
KEEP 
$0.7189 
↓4.0% 
$1.07M
EWT 
$16.354 
↓4.3% 
$768K
MLN 
$85.518 
↓4.3% 
$674K
PAXG 
$1741.0 
↓1.0% 
$663K
BAL 
$51.182 
↓1.2% 
$600K
REPV2 
$46.957 
↓4.2% 
$367K
GNO 
$172.93 
↓0.03% 
$292K
TBTC 
$60697. 
↓0.8% 
$50.2K



#####################. Trading Volume by Asset. ##########################################

Trading Volume by Asset


The figures below break down the trading volume of the largest, mid-size, and smallest assets. Cryptos are in purple, fiats are in blue. For each asset, the chart contains the daily trading volume in USD, and the percentage of the total trading volume. The percentages for fiats and cryptos are treated separately, so that they both add up to 100%.

Figure 1: Largest trading assets: trading volume (measured in USD) and its percentage of the total trading volume (April 12 2021)



Figure 2: Mid-size trading assets: (measured in USD) (April 12 2021)



Figure 3: Smallest trading assets: (measured in USD) (April 12 2021)



#####################. Spread %. ##########################################

Spread %


Spread percentage is the width of the bid/ask spread divided by the bid/ask midpoint. The values are generated by taking the median spread percentage over each minute, then the average of the medians over the day.

Figure 4: Average spread % by pair (April 12 2021)



.


#########. Returns and Volume ############################################

Returns and Volume


Figure 5: Returns of the four highest volume pairs (April 12 2021)


Figure 6: Volume of the major currencies and an average line that fits the data to a sinusoidal curve to show the daily volume highs and lows (April 12 2021)



###########. Daily Returns. #################################################

Daily Returns %


Figure 7: Returns over USD and XBT. Relative volume and return size is indicated by the size of the font. (April 12 2021)



###########. Disclaimer #################################################

The values generated in this report are from public market data distributed from Kraken WebSockets api. The total volumes and returns are calculated over the reporting day using UTC time.

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://blog.kraken.com/post/8612/kraken-daily-market-report-for-april-12-2021/

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Blockchain

Bitcoin Prepares For its Next Move: Where is the 100 SMA, the Key BTC Level?

Republished by Plato

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Bitcoin price is consolidating above the $59,500 support zone against the US Dollar. BTC is now showing a few positive signs, but it must clear $61,200 for a fresh rally in the near term.

  • Bitcoin is holding gains above the $60,000 and $59,500 support levels.
  • The price is now trading well above the $59,500 level and the 100 hourly simple moving average.
  • There is a key bullish trend line forming with support near $59,400 on the hourly chart of the BTC/USD pair (data feed from Kraken).
  • The pair is likely to start a sharp upward move once it clears the $60,800 and $61,200 levels.

Bitcoin Price is Showing Positive Signs

Bitcoin remained in a range above the $59,000 level and it is showing a few positive signs. Recently, BTC made another attempt to clear the $61,200 resistance, but it failed.

It corrected lower and retested the $59,500 support level. A low is formed near $59,432 and the price is now moving higher. It is also trading well above the $59,500 level and the 100 hourly simple moving average.

There was a break above the 50% Fib retracement level of the recent decline from the $61,212 high to $59,432 low. There is also a key bullish trend line forming with support near $59,400 on the hourly chart of the BTC/USD pair.

Bitcoin Price

Source: BTCUSD on TradingView.com

Bitcoin is now trading above $60,400, but it is facing resistance near $60,800. It is close to the 76.4% Fib retracement level of the recent decline from the $61,212 high to $59,432 low.

A successful break above the $60,800 level could open the doors for a move above $61,200. If the bulls succeed in clearing $61,200, the price could rally in the coming sessions.

Dips Limited in BTC?

If bitcoin fails to climb above $60,800 and $61,200, there could be a short-term downside correction. An initial support on the downside is near the $60,000 level.

The main support is now forming near the trend line, $59,500 and the 100 hourly simple moving average. If the bulls fail to protect the 100 hourly SMA, there could be a major decline. In this case, the price might decline towards the $58,000 level.

Technical indicators:

Hourly MACD – The MACD is now gaining momentum in the bullish zone.

Hourly RSI (Relative Strength Index) – The RSI for BTC/USD is now well above the 50 level.

Major Support Levels – $59,500, followed by $59,000.

Major Resistance Levels – $60,800, $61,200 and $62,000.

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://www.newsbtc.com/analysis/btc/bitcoin-prepares-for-next-move-61k/

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Blockchain

USDT, USDC, and BUSD represent 93% of stablecoin market cap

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Research from on-chain analytics provider Glassnode has revealed that the top three stablecoins represent more than 90% of the sector’s entire market cap.

Glassnode’s April 13 “Week On-chain” report found that the top three stablecoins — Tether (USDT), USD Coin (USDC), and Binance USD (BUSD) — have seen significant growth over the past six months to represent a combined capitalization of more than $60 billion, equal to 92.75% of the stablecoin market.

By contrast, six months ago the combined stablecoin capitalization for those three was less than one-third of its current levels at $19.2 billion. This time last year, stablecoins were worth just $7 billion combined.

The analysis compared the growth of stablecoins with Bitcoin’s market cap, identifying a clear correlation between the two. The report also found that USDT’s supply has continued to increase during recent weeks despite BTC trending sideways, whereas growth for USDC and BUSD has slowed.

BTC market cap vs stablecoin supply: Glassnode

The report notes historic lows for its Stablecoin Supply Ratio (SSR) metric, which measures Bitcoin’s market cap relative to the total stablecoin supply to estimate the global “buying power” of the stablecoin sector.

When BTC prices are low, the supply of stablecoins can buy a larger portion of it to push prices up. Conversely, as prices increase the available stablecoins can purchase less which reduces the influence on prices. Glassnode concluded:

“The growth of stablecoin supplies throughout 2020-21 has held the SSR metric near historical lows suggesting a relatively high buying power of digitally native dollars. The demand for digital dollars appears to be keeping pace with demand for Bitcoin and cryptocurrencies as a whole.”

Tether’s market cap has over doubled since the beginning of 2021 to currently sit at a record $45.6 billion, according to the Tether transparency report. Circle’s website reported an all-time high of $11.5 billion USDC on April 9, while Goingecko estimated BUSD’s supply to be $5.1 billion on April 13.

On April 7, Circle CEO Jeremy Allaire predicted its USDC stablecoin could soon surpass PayPal by settlement value.

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://cointelegraph.com/news/usdt-usdc-and-busd-represent-93-of-stablecoin-market-cap

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