Jade to the Max

Jade to the Max is the platinum-selling debut album by American R&B group Jade, released in 1992. The album produced the hit singles "I Wanna Love You" (U.S. #16), "Don't Walk Away" (U.S. #4), "One Woman" (U.S. #22), and "Looking for Mr. Do Right" (U.S. #69). It also contains covers of two songs by the 1970s R&B trio The Emotions – "Don't Ask My Neighbor" and "Blessed".

Jade to the Max
Studio album by
Jade
ReleasedNovember 17, 1992
Recorded19911992
StudioOasis Recording Studios
(Canoga Park, California)
The Post Complex
(Los Angeles, California)
Genre
Length52:21
Label
ProducerVassal Benford
Ron Spearman
Alton "Wokie" Stewart
Jade chronology
Jade to the Max
(1992)
BET's Listening Party
(1993)
Singles from Jade to the Max
  1. "I Wanna Love You"
    Released: September 1, 1992
  2. "Don't Walk Away"
    Released: November 23, 1992
  3. "One Woman"
    Released: 1993
  4. "Looking for Mr. Do Right"
    Released: 1993
Professional ratings
Review scores
SourceRating
Allmusic [1]

The album peaked at #56 on the Billboard 200, #19 on the Top R&B/Hip-Hop Albums, and #10 on the Top Heatseekers.

Track listing

  • Credits adapted from liner notes[2]
No.TitleWriter(s)Length
1."Don't Walk Away"Vassal Benford, Ronald Spearman, Stevie Wonder4:44
2."I Wanna Love You"Benford, Spearman4:31
3."I Want 'Cha Baby"Benford, Spearman4:30
4."That Boy"Benford, Carol Duboc4:03
5."Out with the Girls"Benford, Spearman4:03
6."Hold Me Close"Benford, Tony Haynes4:26
7."One Woman"Benford, Spearman4:49
8."Give Me What I'm Missing"Joi Marshall, Myron McKinley, Angela Slates5:11
9."Looking for Mr. Do Right"Alton "Wokie" Stewart6:17
10."Don't Ask My Neighbor"Skip Scarborough4:17
11."Blessed"Jerry Peters, Maurice White5:30

Personnel

Jade

  • Joi Marshall – vocals
  • Tonya Kelly – vocals
  • Di Reed – vocals

Personnel

  • Vassal Benford – keyboards, multi-instruments
  • Emzie Parker, Jr. – guitars
  • Gerald Albright – saxophone
  • Lanar Brantley – bass
  • Ronald Spearman – drum and keyboard programming
  • Victor Flores – recording engineer, mixing
  • Conley Abrams – recording engineer, mixing
  • Cassandra Mills – executive producer
  • Steve Hall – mastering
gollark: > `x = _(int(0, e), int(e, е))`You may note that this would produce slices of 0 size. However, one of the `e`s is a homoglyph; it contains `2 * e`.`return Result[0][0], x, m@set({int(e, 0), int(е, e)}), w`From this, it's fairly obvious what `strassen` *really* does - partition `m1` into 4 block matrices of half (rounded up to the nearest power of 2) size.> `E = typing(lookup[2])`I forgot what this is meant to contain. It probably isn't important.> `def exponentiate(m1, m2):`This is the actual multiplication bit.> `if m1.n == 1: return Mаtrix([[m1.bigData[0] * m2.bigData[0]]])`Recursion base case. 1-sized matrices are merely multiplied scalarly.> `aa, ab, ac, ad = strassen(m1)`> `аa, аb, аc, аd = strassen(m2)`More use of homoglyph confusion here. The matrices are quartered.> `m = m1.subtract(exponentiate(aa, аa) ** exponentiate(ab, аc), exponentiate(aa, аb) ** exponentiate(ab, аd), exponentiate(ac, аa) ** exponentiate(ad, аc), exponentiate(ac, аb) ** exponentiate(ad, аd)) @ [-0j, int.abs(m2.n * 3, m1.n)]`This does matrix multiplication in an inefficient *recursive* way; the Strassen algorithm could save one of eight multiplications here, which is more efficient (on big matrices). It also removes the zero padding.> `m = exponentiate(Mаtrix(m1), Mаtrix(m2)) @ (0j * math.sin(math.asin(math.sin(math.asin(math.sin(math.e))))), int(len(m1), len(m1)))`This multiples them and I think also removes the zero padding again, as we want it to be really very removed.> `i += 1`This was added as a counter used to ensure that it was usably performant during development.> `math.factorial = math.sinh`Unfortunately, Python's factorial function has really rather restrictive size limits.> `for row in range(m.n):`This converts back into the 2D array format.> `for performance in sorted(dir(gc)): getattr(gc, performance)()`Do random fun things to the GC.
gollark: > `globals()[Row + Row] = random.randint(*sys.version_info[:2])`Never actually got used anywhere.> `ε = sys.float_info.epsilon`Also not used. I just like epsilons.> `def __exit__(self, _, _________, _______):`This is also empty, because cleaning up the `_` global would be silly. It'll be overwritten anyway. This does serve a purpose, however, and not just in making it usable as a context manager. This actually swallows all errors, which is used in some places.> `def __pow__(self, m2):`As ever, this is not actual exponentiation. `for i, (ι, 𐌉) in enumerate(zip(self.bigData, m2.bigData)): e.bigData[i] = ι + 𐌉` is in fact just plain and simple addition of two matrices.> `def subtract(forth, 𝕒, polynomial, c, vector_space):`This just merges 4 submatrices back into one matrix.> `with out as out, out, forth:`Apart from capturing the exceptions, this doesn't really do much either. The `_` provided by the context manager is not used.> `_(0j, int(0, 𝕒.n))`Yes, it's used in this line. However, this doesn't actually have any effect whatsoever on the execution of this. So I ignore it. It was merely a distraction.> `with Mаtrix(ℤ(ℤ(4))):`It is used again to swallow exceptions. After this is just some fluff again.> `def strassen(m, x= 3.1415935258989):`This is an interesting part. Despite being called `strassen`, it does not actually implement the Strassen algorithm, which is a somewhat more efficient way to multiply matrices than the naive way used in - as far as I can tell - every entry.> `e = 2 ** (math.ceil(math.log2(m.n)) - 1)`This gets the next power of two in a fairly obvious way. It is used to pad out the matrix to the next power of 2 size.> `with m:`The context manager is used again for nicer lookups.> `Result[0] += [_(0j, int(e, e))]`Weird pythonoquirkiness again. You can append to lists in tuples with `+=`, but it throws an exception as they're sort of immutable.> `typing(lookup[4])(input())`It's entirely possible that this does things.
gollark: > `def __eq__(self, xy): return self.bigData[math.floor(xy.real * self.n + xy.imag)]`This actually gets indices into the matrix. I named it badly for accursedness. It uses complex number coordinates.> `def __matmul__(self, ǫ):`*This* function gets a 2D "slice" of the matrix between the specified coordinates. > `for (fοr, k), (b, р), (whіle, namedtuple) in itertools.product(I(*int.ℝ(start, end)), enumerate(range(ℤ(start.imag), math.floor(end.imag))), (ǫ, ǫ)):`This is really just bizarre obfuscation for the basic "go through every X/Y in the slice" thing.> `out[b * 1j + fοr] = 0`In case the matrix is too big, just pad it with zeros.> `except ZeroDivisionError:`In case of zero divisions, which cannot actually *happen*, we replace 0 with 1 except this doesn't actually work.> `import hashlib`As ever, we need hashlib.> `memmove(id(0), id(1), 27)`It *particularly* doesn't work because we never imported this name.> `def __setitem__(octonion, self, v):`This sets either slices or single items of the matrix. I would have made it use a cool™️ operator, but this has three parameters, unlike the other ones. It's possible that I could have created a temporary "thing setting handle" or something like that and used two operators, but I didn't.> `octonion[sedenion(malloc, entry, 20290, 15356, 44155, 30815, 37242, 61770, 64291, 20834, 47111, 326, 11094, 37556, 28513, 11322)] = v == int(bool, b)`Set each element in the slice. The sharp-eyed may wonder where `sedenion` comes from.> `"""`> `for testing`> `def __repr__(m):`This was genuinely for testing, although the implementation here was more advanced.> `def __enter__(The_Matrix: 2):`This allows use of `Matrix` objects as context managers.> `globals()[f"""_"""] = lambda h, Ĥ: The_Matrix@(h,Ĥ)`This puts the matrix slicing thing into a convenient function accessible globally (as long as the context manager is running). This is used a bit below.
gollark: * desired
gollark: I can write some code for this if desisred.

References

  1. Cooper, William. Jade to the Max > review at AllMusic. Retrieved 2012-10-14.
  2. Jade - Jade To The Max (CD liner notes). Giant/Reprise Records 7599-24466-2
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